Total 2,275 construction engineer job vacancies in Information Technology category

Senior Software Engineer - eOps (Day of Ops)

Role Overview

The Senior Software Engineer is responsible for delivering and managing SIA's Air-to-Ground digital products through technical excellence, infrastructure engineering, and DevOps practices. This role drives business outcomes by designing, implementing, and maintaining cloud and on-premises solutions while ensuring security, compliance, and operational stability for aviation connectivity systems.

Key Responsibilities

Technical Delivery & Infrastructure Engineering

- Design, implement, and manage complex AWS cloud infrastructure and on-premises systems for Air-to-Ground connectivity products

- Lead infrastructure setup for critical aviation systems including firewall configuration, networking, database management, and security protocols

- Develop and maintain CI/CD pipelines, deployment strategies, and platform delivery frameworks

- Implement air-to-ground communication security configurations including cockpit-to-ground data protection protocols

- Drive cloud migration initiatives and infrastructure modernization projects

Product & Platform Management

- Serve as Technical Lead for Air-to-Ground products including SITA Aircom, Mission Watch (MMT), Airbus and Boeing connectivity systems

- Manage infrastructure setup and configuration for current and new fleet introductions

- Coordinate and execute continuous software upgrades from OEMs (Airbus, Boeing, SITA)

- Plan and implement change requests, disaster recovery tests, and regular server patching activities

- Ensure integration of secure-by-default patterns and compliance controls

Stakeholder & Vendor Management

- Collaborate with SIA Infrastructure teams, Business Units (Engineering, Flight Ops, TMM), and external OEMs

- Manage vendor relationships and technical interfaces with Boeing, Airbus, and SITA

- Translate business needs into technical specifications and measurable acceptance criteria

Operations & Support

- Provide ongoing technical support and troubleshooting for production Air-to-Ground applications

- Implement monitoring, telemetry, and analytics for operational visibility

- Diagnose and resolve infrastructure and application issues

- Create and maintain comprehensive technical documentation and knowledge repositories

Required Qualifications & Experience

Technical Skills:

- Advanced expertise in AWS cloud services (EC2, VPC, IAM, networking, security)

- Strong knowledge of infrastructure as code, CI/CD tools, and DevOps practices

- Proficiency in firewall, network security, and database management

- Experience with Linux/Unix system administration and scripting

- Familiar with Gen AI SDLC (Software Development Life Cycle) and Github Copilot

- Familiar with Java programming and Shell scripts

- Understanding of aviation/connectivity systems (preferred)

Experience:

- Minimum 5 years of software engineering or infrastructure engineering experience

- Minimum 2 years of experience with Airlines Air-to-Ground systems

- Proven track record in delivering complex cloud and on-premises solutions

- Experience managing vendor relationships and technical integrations

- Demonstrated ability to lead technical projects and serve as subject matter expert

Competencies:

- Strong problem-solving and analytical skills

- Excellent collaboration and stakeholder management abilities

- Self-motivated with a positive, can-do attitude

- Ability to work with cross-functional teams and external partners

- Strong technical documentation and communication skills

Software Test Engineer (Java | Testing | AI-Driven Systems)

Experience: 5–8 Years (Mid-Level)

Fixed Term Contract -2 years [Renewable]

About Akkodis

Akkodis is a global digital engineering leader with over 50,000 experts across 30 countries. We drive innovation across mobility, software, robotics, AI, and data analytics—helping organizations accelerate digital transformation and build smarter, more sustainable futures.

Role Overview

This role is ideal for engineers who enjoy a balanced mix of development, testing, and innovation initiatives. While Java programming is required, it will form approximately 30% of the role, with a stronger emphasis on testing, automation, AI-driven initiatives, and technical documentation.

What You’ll Do

• Contribute to embedded software development using Java and OOP principles (~30% of role)
• Lead and support testing, validation, and debugging activities across complex systems
• Design and execute test strategies, automation frameworks, and validation processes
• Leverage AI-driven tools and automation to improve testing efficiency and software quality
• Develop and maintain clear technical documentation, test plans, and system specifications
• Work across the full SDLC, including integration, testing, and deployment
• Collaborate within global agile teams to deliver secure, connected embedded and IoT solutions
• Support continuous improvement of engineering practices, tools, and methodologies

What You Bring

• 5–8 years of experience in software or embedded systems environments
• Strong foundation in Java and Object-Oriented Programming (OOP)
• Proven experience in testing, debugging, and quality engineering
• Hands-on exposure to:
• Git (version control)
• JIRA (issue tracking)
• Jenkins or similar tools (CI/CD, automation)
• Experience working on medium to large-scale systems
• Comfortable working in complex, fast-paced environments with cross-functional teams
• Strong documentation and communication skills

Nice to Have

• Experience in test automation frameworks or QA engineering
• Exposure to AI/ML-driven testing or automation initiatives
• Background in embedded systems, IoT, or secure connected devices

Why Join Us

• Work at the intersection of testing, AI, and next-gen embedded systems
• Be part of a global engineering ecosystem
• Gain exposure to innovation-driven projects beyond pure development
• Build expertise in automation, quality engineering, and AI-led transformation

Don't miss out on this chance to be a part of a dynamic and growing team. Take the Next Step in your career journey with us!

• To apply, please submit your updated resume along with your notice period. [ We are looking for someone to start ASAP]
• Click on the 'Apply here' button to drop your resume directly or email it to susmita.SAHU@akkodis.com
• Our team will review all applications and contact shortlisted candidates for further steps in the selection process.

Job Benefits

• Competitive salary with performance bonuses (AWS + VB)
• Opportunity to work with a leading MNC in the semiconductor industry
• Exposure to advanced technologies (automation, AI/ML, computer vision)
• Structured training and career progression
• Stable work environment with strong engineering support

Job Responsibilities

• Design and develop high-performance software for semiconductor equipment, including motion control and automation systems
• Develop and implement embedded and real-time software for high-speed, high-precision machines
• Collaborate with cross-functional teams (software, electronics, mechanical, product) for system integration
• Perform software testing, debugging, and optimization to ensure system reliability and performance
• Develop control algorithms, servo systems, and support advanced technologies such as AI/ML or computer vision where applicable
• Maintain technical documentation and support internal teams with training and troubleshooting
• Ensure compliance with quality, safety, and industry standards

Job Requirements

• Degree in Computer Science, Software Engineering, Electrical Engineering, or related discipline
• Proficiency in C++ for embedded systems, automation, or industrial applications
• Experience in software development within semiconductor, automation, or manufacturing environments preferred
• Strong analytical and problem-solving skills with ability to troubleshoot complex systems
• Familiarity with motion control systems, real-time programming, or AI/ML/computer vision is an advantage

Please submit your updated resume in MS Word format via the "Apply Now" button.

We regret that only shortlisted candidates will be notified.

StaffKing Pte Ltd (20C0358) | Stanley Chin (R24124684)

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Senior Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Bank , Post Trade Technology Group, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems

• Develops secure high-quality production code, and reviews and debugs code written by others

• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

• Leads evaluation sessions with business stakeholders, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

Required qualifications, capabilities, and skills

• Bachelor's degree in Computer Science or equivalent

• Formal training or certification on engineering concepts and 5+ years applied experience in software engineering

• Hands-on practical experience delivering system design, application development, testing, and operational stability

• Advanced in one or more programming language(s)

• Proficiency in automation and continuous delivery methods

• Proficient in all aspects of the Software Development Life Cycle

• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

• Proficient in full stack development skill Java 21, REACT or any other frameworks , building into Public Cloud and CD/CD strategies.

Preferred qualifications, capabilities, and skills

• In-depth knowledge of the financial services industry and their IT systems

• Practical cloud native experience

To apply for this position, please use the following URL:

https://ars2.equest.com/?response_id=0790f3558ca7189aa57af5238df75528

The Opportunity

Join a team building the data foundations that support the firm’s AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm.

At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform.

This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases, and may also help extend platform tooling where additional functionality is needed.

Role Summary

As a Data Engineer in the Lakehouse and AI Data Platform team, you will design, build, test and support data pipelines and curated datasets on the firm’s modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose.  Where there are gaps in platform functionality, you may also contribute to shared tooling or framework components that improve how the platform is used and operated.

The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases.

Key Responsibilities

Pipeline Engineering

• Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform.
• Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability.
• Where needed, build reusable tooling to improve delivery, consistency and operational support.
• Ensure data pipelines are production-ready, well tested and operationally supportable.

Data Modelling and Curation

• Develop raw, refined and curated datasets that support analytics, reporting and AI use cases.
• Apply sound data modelling principles to represent business entities, relationships and historical change accurately.
• Work with consumers to shape data products that are usable, well documented and aligned to business needs.

Data Quality and Reconciliation

• Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets.
• Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise.
• Contribute to clear standards for testing, monitoring and issue resolution.
• Contribute to practical improvements in testing, monitoring or reconciliation tooling where these strengthen platform reliability and day-to-day delivery.

Delivery and Partnership

• Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations.
• Communicate clearly on progress, risks, dependencies and design choices, including where delivery would benefit from improvements to shared platform tooling.
• For more senior candidates, take a broader role in technical leadership, task breakdown and support for junior engineers.

Skills and Experience

Required

• Bachelor’s or master’s degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise.
• Strong hands-on programming experience in Python or Java.
• Good working knowledge of SQL, including troubleshooting, optimization and data analysis.
• Ability to learn new tools, internal platforms and delivery workflows quickly.
• Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices.

Data Engineering Capability

• Understanding of temporal data modelling, including the handling of historical state and change over time.
• Knowledge of schema design, schema evolution and data compatibility considerations.
• Understanding of partitioning, clustering and other techniques used to improve data performance at scale.
• Ability to make sensible design choices across normalized and denormalized models, and between natural and surrogate keys.
• Practical approach to data quality, reconciliation and root-cause analysis.
• Experience building or supporting production data pipelines in a collaborative engineering environment.
• Experience working with distributed data processing frameworks such as Apache Spark.
• Working knowledge of common data formats such as JSON, Avro and Parquet.

Technology Environment

The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies.

Examples of technologies in scope include:

• Data processing and logic: ANSI SQL, Apache Spark, Kafka
• Data formats: JSON, Avro, Parquet
• Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ
• Engineering and deployment: CI/CD tooling, containerized or Kubernetes-based deployment approaches where relevant

You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.

What We Are Looking For
We are looking for engineers who can deliver well-structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast-paced environment where data platforms support important business outcomes. It will also suit candidates who are willing to contribute to shared tooling or platform components that make the wider engineering environment more effective.

Stronger candidates will typically demonstrate:

• sound judgement in technical trade-offs
• attention to detail in data correctness and testing
• a clear and structured approach to problem solving
• willingness to work closely with stakeholders and partner teams
• an ability to identify when delivery problems would be better solved through reusable tooling or platform improvements
• an interest in developing long-term expertise within the firm

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

© The Goldman Sachs Group, Inc., 2026. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

The Opportunity

Join a team building the data foundations that support the firm’s AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm.

At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform.

This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases, and may also help extend platform tooling where additional functionality is needed.

Role Summary

As a Data Engineer in the Lakehouse and AI Data Platform team, you will design, build, test and support data pipelines and curated datasets on the firm’s modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose.  Where there are gaps in platform functionality, you may also contribute to shared tooling or framework components that improve how the platform is used and operated.

The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases.

Key Responsibilities

Pipeline Engineering

• Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform.
• Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability.
• Where needed, build reusable tooling to improve delivery, consistency and operational support.
• Ensure data pipelines are production-ready, well tested and operationally supportable.

Data Modelling and Curation

• Develop raw, refined and curated datasets that support analytics, reporting and AI use cases.
• Apply sound data modelling principles to represent business entities, relationships and historical change accurately.
• Work with consumers to shape data products that are usable, well documented and aligned to business needs.

Data Quality and Reconciliation

• Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets.
• Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise.
• Contribute to clear standards for testing, monitoring and issue resolution.
• Contribute to practical improvements in testing, monitoring or reconciliation tooling where these strengthen platform reliability and day-to-day delivery.

Delivery and Partnership

• Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations.
• Communicate clearly on progress, risks, dependencies and design choices, including where delivery would benefit from improvements to shared platform tooling.
• For more senior candidates, take a broader role in technical leadership, task breakdown and support for junior engineers.

Skills and Experience

Required

• Bachelor’s or master’s degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise.
• Strong hands-on programming experience in Python or Java.
• Good working knowledge of SQL, including troubleshooting, optimization and data analysis.
• Ability to learn new tools, internal platforms and delivery workflows quickly.
• Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices.

Data Engineering Capability

• Understanding of temporal data modelling, including the handling of historical state and change over time.
• Knowledge of schema design, schema evolution and data compatibility considerations.
• Understanding of partitioning, clustering and other techniques used to improve data performance at scale.
• Ability to make sensible design choices across normalized and denormalized models, and between natural and surrogate keys.
• Practical approach to data quality, reconciliation and root-cause analysis.
• Experience building or supporting production data pipelines in a collaborative engineering environment.
• Experience working with distributed data processing frameworks such as Apache Spark.
• Working knowledge of common data formats such as JSON, Avro and Parquet.

Technology Environment

The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies.

Examples of technologies in scope include:

• Data processing and logic: ANSI SQL, Apache Spark, Kafka
• Data formats: JSON, Avro, Parquet
• Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ
• Engineering and deployment: CI/CD tooling, containerized or Kubernetes-based deployment approaches where relevant

You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.

What We Are Looking For
We are looking for engineers who can deliver well-structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast-paced environment where data platforms support important business outcomes. It will also suit candidates who are willing to contribute to shared tooling or platform components that make the wider engineering environment more effective.

Stronger candidates will typically demonstrate:

• sound judgement in technical trade-offs
• attention to detail in data correctness and testing
• a clear and structured approach to problem solving
• willingness to work closely with stakeholders and partner teams
• an ability to identify when delivery problems would be better solved through reusable tooling or platform improvements
• an interest in developing long-term expertise within the firm

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

© The Goldman Sachs Group, Inc., 2026. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

Arch investment Management Ltd. (AIML), based in Bermuda, is a wholly owned subsidiary of Arch Capital Group Ltd., a leading insurance and reinsurance company. Arch Capital has investable assets of over $45 bn. Arch Investment Management manages Arch Capital and its subsidiaries' portfolios.  The continued growth of the company has created the need to fill a new position within our Risk and Quantitative team to help building AIM’s in house AMI web interface.

• Develop and develop high-quality, responsive user interfaces for web and mobile applications. 
• Conduct user research, useability testing, and gather feedback to inform design decisions. 
• Create wireframes, prototypes, and high-fidelity mockups to effectively communicate design concepts. 
• Implement and maintain UI components using modern frontend technologies and framework. 
• Write clean, maintainable, and well-documented code. 
• Optimize applications for maximum speed and scalability. 
• Troubleshoot and debug issues across the entire stack. 
• Participate in code reviews to ensure code quality and best practices. 

Principal Software Engineer, Pune

We are looking for a Principal Software Engineer who defines and drives the technical strategy for large‑scale, distributed, and cloud‑native systems. This role operates at a company and platform level, designing foundational architectures, enforcing engineering standards, and leading complex technical transformations that impact multiple teams and products.

You will act as a technical authority and architect, balancing short‑term delivery needs with long‑term scalability, reliability, security, and cost efficiency. This role requires deep hands‑on expertise in Java, Python, SQL, distributed systems, cloud platforms, and modern DevSecOps practices, along with the ability to guide teams in AI‑driven development and generative tooling adoption.

Responsibilities

• Define and evolve the technical strategy for large‑scale, distributed, and high‑availability systems
• Design foundational platforms, frameworks, and shared services that impact multiple teams
• Lead architectural transformations for legacy systems and large‑scale applications
• Drive system‑wide decisions with a strong focus on scalability, performance, resilience, security, and maintainability
• Translate ambiguous business requirements into robust, future‑proof technical architectures
  
  Platform Governance & Engineering Standards
•  Develop and enforce governance policies for APIs, security, cloud infrastructure, and system integrations
• Define company‑wide best practices for engineering quality, reliability, observability, and efficiency
• Establish architectural guardrails to ensure consistent design and implementation across teams
• Drive adoption of security, compliance, and infrastructure automation best practices
  
  Cloud, DevSecOps & Cost Optimization
•  Establish strategies for cost‑efficient cloud resource utilization, scaling, and performance optimization
• Architect standardized CI/CD frameworks used across multiple teams
• Define DevSecOps guardrails ensuring secure, compliant, and consistent delivery pipelines at scale
• Champion Infrastructure‑as‑Code, automation, and operational excellence
  Data, Streaming & Distributed Systems
•  Provide technical leadership in large‑scale data processing, streaming architectures, and messaging systems
• Design and evolve systems using Kafka, queues, async processing, and event‑driven patterns
• Guide teams on concurrency, fault tolerance, back‑pressure handling, and system resilience
  
  AI & Engineering Innovation
•  Guide teams in AI‑driven development practices, including the responsible use of Generative AI tooling
• Evaluate AI and GenAI technologies for quality, scalability, security, and real business value
• Design and integrate AI/ML capabilities into systems from a platform and application engineering perspective
• Champion innovations that improve developer productivity, automation, and engineering efficiency
  Technical Leadership & Collaboration
•  Act as a technical mentor and design authority for senior and mid‑level engineers
• Engage in deep technical problem‑solving, influencing system‑wide technical decisions
• Collaborate closely with Product, Security, Operations, and Platform teams
• Lead by example through hands‑on design reviews, architectural guidance, and complex issue resolution
  
  Required Technical Skills: Core Engineering 
•  Java (Spring Boot, REST, Microservices, JVM internals)
• Python (core Python, scripting, automation, data processing)
• SQL (advanced querying, schema design, performance tuning)
• Strong knowledge of Data Structures, Algorithms, and System Design
• Scripting languages (Shell, Bash, or similar)
  
  Systems & Platforms
• Distributed systems, concurrency, fault tolerance, scalability patterns
• Cloud platforms (Azure / AWS / GCP) and cloud‑native architectures
• Containers and orchestration (Docker, Kubernetes)
• CI/CD, DevSecOps, Infrastructure‑as‑Code
• Messaging and streaming systems (Kafka, event‑driven architectures)
  
  AI / Data (Working Knowledge)
• Experience integrating AI/ML or GenAI APIs into production systems
• Understanding of data pipelines, model deployment, and operational AI concerns
• Ability to assess where AI adds value versus unnecessary complexity

Key Responsibilities

• Design and implement backend modules using Java and related frameworks

• Develop and maintain APIs to support system integration

• Write efficient, reusable, and testable code following best practices

• Troubleshoot application defects and implement long-term fixes

• Optimize application performance and database interactions

• Participate in technical design discussions and code reviews

• Collaborate with frontend, QA, and infrastructure teams for seamless releases

• Maintain technical documentation and contribute to continuous improvements

Required Qualifications

• Degree in Computer Science, Information Technology, or equivalent experience

• 3–5 years of hands-on Java development experience

• Strong knowledge of object-oriented programming principles

• Experience with Spring, RESTful services, and backend integration

• Familiarity with SQL databases and query optimization

• Understanding of version control systems such as Git

• Strong analytical and debugging skills

Job Purpose: Product PCB Design & PCB layout

Key Responsibilities:

• Perform instrumentation and products/module development.
• Design and develop PCB layouts using software like Altium Designer.
• Create schematics, developing PCB layouts, collaborating with Hardware Engineer and Mechanical Engineer, testing, and debugging PCB.
• PCB design includes analogy, digital, LCD Display, Audio, Sensors, RF, and power charging components etc.
• Ensure compliance with PCB manufacturing processes and design rules.
• Generate and manage PCB documentations such as Gerber, ODB, BOM, fab and assembly drawings delivery for fabrication.
• Work with manufacture vendor to seek assembly design requirements, resolve DFM and manufacturing related issues.
• Improve PCB design processes.
• Maintaining and expanding the company PCB libraries.
• Support transfer of products to production.
• Support and manage factory production test and relative engineering activities.

Knowledge And Skill Requirements:

• Bachelor's degree with 3 years and above experience of PCB layout design.
• Familiar with schematic and layout tools such as Altium Designer.
• Knowledge of PCB fabrication and assembly techniques and standards.
• Able to operate electronic equipment such as oscilloscope, logical analyser, spectrum analyser, network analyser.
• Knowledge of signal integrity, power integrity, EMC, and EMI issues and solutions.
• Experience in cost effective consumer electronics design.
• Good communication skill.
• Ability to work independently and as part of a team.

Working Conditions:

- Working conditions are normal for an office environment.

- Work requires willingness to work a flexible schedule.

Role Summary

The Data Engineer will support the design, development, and operation of modern data systems and infrastructure for Data Programme. The role involves building scalable and secure data platforms, developing production-grade data pipelines, and enabling analytics, AI, and machine learning use cases across the ecosystem.

The candidate is expected to work closely with Product Managers, Data Scientists, engineers, and business stakeholders to deliver reusable, maintainable, and secure data solutions that support digital transformation objectives.

Key Responsibilities

1. Data Systems and Architecture

• Design, develop, and maintain end-to-end data systems and supporting architecture
• Build and integrate database systems, backend services, and infrastructure components to support business and analytical use cases
• Ensure solutions are designed with strong consideration for scalability, maintainability, reusability, and security
• Contribute to architecture and engineering decisions for data platforms and services

2. Data Engineering and Pipeline Development

• Develop and maintain production-grade ETL / ELT pipelines for ingestion, transformation, and delivery of data
• Build and administer databases and supporting data services for operational and analytical workloads
• Support reliable and efficient data workflows for reporting, analytics, data science, and machine learning applications
• Monitor, troubleshoot, and optimise data processing jobs, database operations, and pipeline performance

3. Cloud, DevOps and Infrastructure

• Develop infrastructure and services using modern cloud engineering practices
• Support backend, infrastructure, deployment, and operational components required for data systems
• Contribute to automation, CI/CD, monitoring, and operational readiness of data platforms
• Ensure secure and resilient deployment practices across environments

4. Cross-functional Delivery

• Work closely with Product Managers, Data Scientists, users, and other engineers to ensure solutions meet user and organisational needs
• Partner with policy and business divisions to support digital transformation initiatives through data and AI methods
• Translate requirements into implementable technical designs and engineering work items
• Participate actively in iterative product and platform delivery

5. Documentation and Support

• Document system designs, architecture decisions, data flows, and operational procedures
• Support knowledge transfer, maintainability, and operational support for delivered solutions
• Collaborate effectively across multidisciplinary teams and contribute to healthy engineering practices
• Support issue investigation, troubleshooting, and enhancement of production systems

Mandatory Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience
• Experience in data systems and architecture development, including databases, backend services, DevOps, and infrastructure engineering
• Experience developing and administering production-grade databases and data pipelines
• Strong understanding of scalable, secure, and maintainable engineering practices
• Strong communication and collaboration skills
• Interest in working on public good and supporting digital transformation in the education domain

• Experience with modern cloud-based data engineering environments
• Experience with backend development and system integration
• Experience with frontend development
• Exposure to data science and machine learning applications
• Familiarity with DevOps, CI/CD, infrastructure automation, and monitoring practices
• Experience working in agile, cross-functional product teams
• Experience in public sector, education, or mission-driven digital delivery environments

Seniority Expectations

Associate Consultant (1-3 Years)

• Supports design, development, and maintenance of data systems under guidance
• Contributes to data pipelines, database tasks, and operational support activities
• Demonstrates sound technical fundamentals and willingness to learn

Consultant (4-6 Years)

• Works independently on assigned engineering tasks and modules
• Designs and develops data pipelines, databases, and infrastructure components of moderate complexity
• Participates actively in technical discussions and cross-functional delivery

Senior Consultant (7 Years and above)

• Takes ownership of end-to-end system and architecture components
• Leads design and implementation of scalable, secure, and reusable data platforms
• Supports technical decision-making and mentors junior team members where needed
• Engages confidently with cross-functional stakeholders across product, business, and technical teams

Key Responsibilities:

• Manage RFQ, NPD, NPI, FA and Product Transfer.

• Prepare requisition for order, review supplier offers, make technical bid evaluation if required.

• Liaise and coordinate with customers and other departments pertaining to project activities and order fulfilment

• Work closely with customers on audit, engineering change order

• Responsible for projects transferred from development to operations, ensuring that documents and procedures are in place to independently handle repeat sales orders.

• Monitor and manage Suppliers’ performance to meet delivery, cost and quality targets

• Identify and mitigate program risks and implement risk mitigation plans

• Collaborate with cross-functional team members to meet Key Performance Indicators and Operational deliverables.

• Lead the development of simulation test cases for the verification of process change initiatives.

• Utilize manufacturing and/or business operations experience to quickly frame the operational challenge and visualize a solution

• Support Design, Engineering activities of the day-to-day operations.

• Responsibility & coordination of the complete certification process from application to approval for products

• Creation of technical documentation, e.g. technical drawings (2D drawings and 3D models)

• Knowledge of the supplier landscape and the materials (knowledge of who can manufacture which product)

• Ensuring product compliance, enforce quality assurance protocols and standards

Skills & Qualification:

• Degree/Diploma/Higher Nitec in Electronics/Mechanical/Mechatronics Engineering

• Minimum 1 - 2 years of relevant experience in a manufacturing industry,. Contract manufacturing background will be at advantage

• Experience in communicating with contract manufacturers / suppliers

• Must able to analyse technical drawing/specification

• Experience in SAP system is a plus

• Strong communication and program management skills

• Addresses present issues immediately and independently

• Possess self-confident and willing to share opinions and expertise in discussions

• Able to communicate to all levels in the organization

• Provide support to colleagues in the department and work as a team to achieve departmental goals & targets

Role : System Engineer (LabX)

We invite highly motivated individuals to join our team in providing support to our clients’ biomanufacturing facilities. In this role, you will be tasked with performing System engineer with qualification and System Administration for LabX software application at Client facility and ensuring strict adherence to pharmaceutical GMP and regulatory standards.

Job Description (JD):

1. Serve as the System Administrator for LabX software
2. Oversee and manage all method modifications within LabX
3. Lead the qualification of new laboratory equipment (e.g., pH and conductivity meters) integrated with LabX
4. Manage change control processes in compliance with quality standards
5. Maintain and manage CSV (Computer System Validation) documentation 

Timeline: 1 year contract

As a software engineer, you will be part of an international Scrum team that uses agile standard methodologies to build stable and maintainable software.

You will apply the latest techniques in C++ and C# software design to develop software that ranges from machine control up till modern WPF user interfaces.

You will have the opportunity to occasionally travel to customers and discover new places and cultures along the way.

Monthly team training sessions and access to online learning portals will ensure that your knowledge stays up-to-date and allow you to grow beyond your current know-how.

From on the edge software development, designing advanced machines, defining and implementing image processing algorithms or crafting new ways to do optical inspections, we do it all, and we need your talent to keep going one step beyond!

Minimum Qualifications

• Minimum Bachelor's Degree in Engineering and 5 years of experience
• Experience with C++ software development
• Knowledge of object-oriented design, design patterns, and UML
• An affinity to automation. Knowledge of PLC programming is a plus
• Knowledge of C#, WPF, Python, GIT and Scrum are a plus
• Strong communication, analytical, and problem-solving skills