• Installing/de-installing/relocating all distributed systems and network hardware (CSUs, DSUs, routers, switches, encryptors, firewalls, etc.) in the Americas Data Centers within the internal service level mandates.
• Installing/de-installing/extending/relocating/testing all carrier circuits to the network hardware.
• Installing/de-installing/relocating all patch cabling for systems and network hardware.
• Installing/de-installing/relocating all Data Center hardware.
• Assist with the coordination of cabinet power, circuit and patch infrastructure installations with various facilities, electrical and communications vendors.

Skills/Requirement

• Experience in the implementation, maintenance and analysis of data center facilities, hardware, communications infrastructure, strategies, tools and effective troubleshooting techniques.
• Basic background on enterprise data center facilities and infrastructure environments.
• In-depth knowledge of complex, Enterprise class inter-networked environments involving a combination of switched/routed/shared Ethernet.
• Strong knowledge of WAN technologies (OC-x, DS-x), subnetting and TCP/IP protocol is a must.
• Excellent communication and writing skills are a must.
• Knowledge of trouble ticketing systems, change control, Project processes and associated tools.
• Logical problem-solving techniques and associated experience in system, data center facilities and telecommunications.
• Experience with project management.
• Financial Services industry knowledge is a plus.

Responsibilities:

• To support and deliver any activities which required 24x7
• To support Service Request, Incident and Change activities
• To support and deliver requested Daily Infra Operations activities
• To support and deliver requested Environment Operations activities
• To support and deliver requested task from Projects team
• To support and deliver requested task from IT Initiative Projects
• To support, coordinate, monitor and supervise any external vendor working in restricted facilities

Requirements:

• Minimum of 1-3 years hands-on experience in providing Data Center support
• Minimum 1-3 years of cabling experience (preferably structured cabling)
• Degree or diploma in IT would be an advantage
• Ability to work independently with minimal supervision
• Able to communicate messages clearly and concisely
• Ability to maintain high-quality performance and constantly deliver results in a timely manner

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Infrastructure Management

• Manage and maintain complex cloud environments for AI workloads.
• Ensure secure, stable connectivity between internal systems and AI platforms.
• Perform ongoing system maintenance and monitoring to guarantee optimal AI model performance.
• Implement and maintain security protocols for AI data handling and model deployment.

Rapid Prototyping & Technical Validation

• Conduct technical due diligence for new AI technologies, frameworks, and vendor solutions.
• Build proof-of-concepts to validate AI model feasibility and performance.
• Perform stress-testing of AI vendor APIs, model endpoints, and third-party integrations.
• Document technical findings and provide recommendations for AI technology adoption.

Pipeline Development & AI Infrastructure

• Develop and maintain automated data pipelines for AI model training and inference.
• Write robust code to ensure reliable data movement from source systems to AI models.
• Implement MLOps practices for model deployment, monitoring, and maintenance.
• Build and maintain AI model serving infrastructure and API endpoints.

Must-Have Requirements

• Bachelor’s degree in Computer Science, Data Science, AI/Machine Learning, or related technical field.
• 3+ years of experience in AI/ML engineering or related technical roles.
• Strong programming skills in Python, with experience in AI/ML libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with cloud infrastructure management (AWS, Azure, or GCP).
• Knowledge of MLOps practices, model deployment, and monitoring.
• Experience with API development and integration for AI services.
• Understanding of data pipeline tools and ETL processes for AI applications.

Role Overview

We are seeking a Data Engineer to design, develop, and maintain scalable, secure, and reliable data platforms and pipelines that support business and operational needs. The successful candidate will work closely with stakeholders, engineers, and data stewards to deliver high-quality data products while ensuring strong governance, security, and operational excellence.

Key Responsibilities

Data Pipeline Development and Architecture

• Translate business and data requirements into technical specifications and scalable data solutions.

• Develop and maintain data products as part of a cross-functional data team.

• Design, build, and optimise data ingestion pipelines to collect, transform, integrate, and harmonise data from multiple source systems.

• Design, develop, test, and maintain reusable data models to support reporting, analytics, and operational use cases.

• Implement secure and efficient mechanisms for users and applications to access enterprise data assets.

• Evaluate and implement new technologies, tools, and processes to enhance data infrastructure capabilities and performance.

Data Quality, Testing and Validation

• Develop and implement data quality controls and validation processes to ensure data accuracy, completeness, and consistency.

• Design, execute, and maintain test cases for data pipelines, including functional, regression, and exploratory testing.

• Build and maintain automated testing frameworks to improve data reliability and reduce production defects.

• Perform data reconciliation and integrity testing to validate end-to-end data processing and transformation workflows.

• Support User Acceptance Testing (UAT) activities by working with stakeholders to validate business requirements and expected outcomes.

Operations, Governance and Continuous Improvement

• Monitor and maintain databases, ETL processes, and data platforms, including performance optimisation, troubleshooting, capacity planning, and operational support.

• Collaborate with technology teams and stakeholders to align infrastructure, security, and platform requirements.

• Support the implementation and enforcement of data governance policies, standards, and best practices.

• Maintain data catalogues, metadata repositories, and data lineage documentation.

• Implement data security controls, including access management, encryption, masking, and other data protection measures.

• Drive continuous improvements in CI/CD, DevOps, and Site Reliability Engineering (SRE) practices.

Requirements

Qualifications and Experience

• Bachelor's Degree in Computer Science, Software Engineering, Information Technology, or a related discipline.

• Strong understanding of system design principles, data structures and algorithms, data modelling, data access patterns, and data storage technologies.

• Experience designing, building, and maintaining batch and real-time data pipelines.

• Hands-on experience with workflow orchestration tools such as Apache Airflow and Azure Data Factory.

• Proficiency in Python, SQL, and Shell scripting.

• Experience working with cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform (GCP).

• Experience with Databricks.

• Experience implementing data quality frameworks, validation processes, and testing methodologies for data pipelines.

• Familiarity with automated testing approaches and integration within CI/CD environments.

• Experience with issue tracking and test management tools such as JIRA or equivalent platforms.

• Familiarity with CI/CD pipelines and DevOps practices.

• Experience using DevOps tools such as Docker, Git, and Terraform.

• Experience implementing solutions that support data security, data quality, and data governance requirements.

Preferred Experience

• Familiarity with government-sector data management, governance, infrastructure, and security frameworks.

• Experience in climate, weather, environmental, or geospatial data domains will be advantageous.

Additional Information

• Appointment level and remuneration will be commensurate with qualifications, skills, and relevant experience.

· 6–8 years of experience in Big Data / Data Platform Engineering in enterprise environments.

· Strong hands-on experience with:

o    Hadoop ecosystem (HDFS, YARN, MapReduce, HDP)

o    Apache Kafka (high-throughput environments)

o    Redis and MongoDBclusters

o    OpenSearch Elasticsearch

o    Apache NiFi

o AWS EMR + good knowledge of AWS Cloud.

· Strong expertise in Linux system administration and scripting (Shell/Python)

· Experience with Kerberos, data security, and access governance

· Proven experience in handling high-volume, low-latency systems (preferably payments/trading)

About Us

Green Link Digital Bank is Singapore's inaugural wholesale digital bank focusing on supply chain finance, mainly serving MSMEs and aiming to help MSMEs grow and improve digitization.

About the Role

The Data Governance Lead plays a pivotal role in shaping and operationalizing enterprise data governance, ensuring our data is well managed, compliant, secure, and ready to power analytics, AI, and digital innovation. This role combines high-level strategic planning with hands-on execution, requiring you to drive data governance adoption across business and technology teams, strengthen data quality, and embed regulatory aligned controls into day-to-day operations.

Responsibilities

• Responsible for establishing and implementing enterprise-wide data governance frameworks, system, policies, and process as regard to the governance, use and analysis of data.
• Translate governance strategy into practical operating models, processes, and controls across the bank.
• Establish and maintain data ownership andstewardship structures across business domains.
• Drive adoption of governance practices withmeasurable improvements in data quality, trust, and compliance.
• Lead governance forums and working groups totrack progress, escalate risks, and resolve issues.
• Define and enforce data quality standards(accuracy, completeness, timeliness, consistency).
• Oversee data quality monitoring, issue management, and remediation workflows.
• Strengthen metadata management, including data cataloguing, lineage, classification, and business glossaries.
• Implement data lifecycle, retention, archival, and disposal policies aligned with MAS and PDPA requirements.
• Ensure governance practices meet MAS guidelines, PDPA, outsourcing requirements, and internal risk frameworks.
• Partner with Risk, Compliance, Legal, and Internal Audit to ensure audit readiness and regulatory compliance.
• Support documentation, traceability, and lineage requirements for regulatory reporting.
• Support implementing AI governance and responsible AI practices.
• Ensure data used for AI/ML is well‑classified, high‑quality, and compliant with ethical and regulatory expectations.
• Partner with business, technology, and operations teams to embed governance into daily processes.
• Provide training, communication, and guidance to uplift data literacy and governance awareness.
• Influence senior stakeholders to prioritise data governance and drive behavioural change.
• Support the rollout and adoption of data governance tools (e.g., data catalogues, quality platforms).
• Promote automation and digitalisation of governance workflows to improve efficiency and transparency.

Requirements

• 8-12 years of experience in data governance, data management, risk, or compliance, preferably in financial services or regulated environments.
• Strong understanding of data risk areas(quality, privacy, security, access, retention).
• Experience implementing governance frameworks, policies, and standards.
• Proven ability to work with cross functional stakeholders across business and technology.
• Familiarity with MAS regulatory expectations, PDPA, and cloud-based data platforms.
• Strong analytical, communication, and stakeholder management skills.
• Experience in digital banking, wholesale banking, or fintech environments.
• ·Exposure to AI/ML governance, data lineage tools, or metadata platforms.
• Certifications such as CDMP, DCAM, TOGAF, or equivalent is a plus

By submitting your application, you have given your consent for us to collect, use and retain your data for a year as according to our prevailing data retention and PDPA policies. Should you have any enquiries on our data policy, please contact us at CustomerSupport@glbank.com.

· Background in engineering, computer engineering, computer science, mathematics, statistics, or equivalent.

· Strong technical knowledge in AI

· Good understanding of the latest research and technologies in AI for productiondeployment

· Strong coding experience in programming languages such as Python and/or C++

· Experience working with libraries for data manipulation, visualization, machine learning, and reporting.

· Hands-on experience with one or more deep learning frameworks, e.g., TensorFlow, Torch

· Extensive experience with OpenAI and Claude code-based prompt engineering.

· Hands-on experience developing and deploying AI agents, RAG and vector/graph databases.

· Strong understanding of 3D geometry, vector math, and coordinate systems

· Experience with algorithms for mesh manipulation, Boolean operations, and geometrictransformations

· Proficiency in relevant 3D modeling or CAD software (e.g., Blender, Rivet) and/or programming libraries (e.g., OpenGL, CGAL, Three.js)

· Team player with the ability to work in a cross-functional team with excellent interpersonal skills

· Strong communication skills, both verbal and written, as well as strong presentation and engagement skills

Responsibilities:

• Data Infrastructure: Build, implement, and maintain scalable data pipelines and storage architectures.
• Data Quality: Maintain strong data integrity by ensuring reliability, consistency, and accuracy across all data processes.
• Performance Optimization: Enhance system efficiency by tuning data processing workflows and improving large-scale performance.
• Process Improvement & Mentoring: Strengthen data engineering practices while providing guidance and support to junior engineers.
• Cross-Functional Collaboration: Partner with business analysts, data scientists, and backend teams to deliver timely and actionable data solutions.

Qualifications:

• 5+ years’ experience in data engineering or backend roles, with strong programming skills in Python or Java/Scala.
• Hands-on experience with big data tools: Spark, Flink, Kafka, Airflow, and cloud platforms (AWS, GCP, Azure); proficient in SQL.
• Skilled in designing and maintaining data models, warehouses, and ETL/ELT pipelines for scalable, reliable systems.
• Knowledgeable in data quality, governance, security, and compliance best practices.

We regret only shortlisted candidates will be contacted. All applications will be handled confidentially. By submitting your application, you agree to the collection, use, retention, and disclosure of your personal information to prospective employers.

Wecruit Pte Ltd
EA License No: 20C0270
EA Personnel: Nyon Hock Sen (Aden)
EA Personnel Reg No: R24124070

Responsibilities:

• Lead and collaborate with data scientists and analysts to drive innovation, knowledge sharing, and continuous improvement.
• Design, develop, and deploy robust analytical and machine learning models using advanced statistical techniques.
• Partner with business and technical stakeholders to identify key challenges and translate them into data-driven solutions.
• Develop dashboards and data visualisations to effectively communicate insights to technical and non-technical audiences.
• Stay current with emerging data science trends, tools, and methodologies, applying relevant advancements where appropriate.
• Contribute to the establishment and enhancement of data governance, data quality, and analytics best practices.

Requirements

• Master’s degree or PhD in Data Science, Statistics, Machine Learning, Computer Science, or a related quantitative discipline.
• Significant hands-on experience in data science or advanced analytics roles, preferably within complex engineering or operational environments.
• Strong proficiency in Python and/or SQL, with experience using machine learning libraries and frameworks.
• Demonstrated ability to manage multiple projects concurrently and deliver high-quality outcomes in a fast-paced setting.
• Strong analytical and problem-solving skills, with the ability to interpret and extract insights from complex datasets.
• Excellent communication and stakeholder engagement skills, with the ability to explain technical concepts clearly to non-technical audiences.
• Familiarity with enterprise systems (e.g. PLM, MES, MRO) and cloud platforms such as AWS will be advantageous.

To submit your application, please apply online to apply@rn-care.com or call +(65) 6513 5697 for private and confidential discussion.

Your interest will be treated with the strictest of confidence. We regret that only shortlisted candidates will be notified or contacted.

RN Care Pte. Ltd
EA License No: 17C8900

About Us:

Tentacle Tech is an IT and software development consulting company serving some of Malaysia's largest enterprises. We deliver technology solutions, software development services, and IT consulting across multiple industries. We are looking for a talented professional to join our growing team in the technology sector.

The Role:

We are seeking an experienced Technical Architect – Data & AI to design and lead the implementation of enterprise-scale Data, Analytics, AI, and Generative AI solutions within the technology sector. You will bridge business requirements and technology, collaborating with stakeholders, data engineers, data scientists, and cloud architects to deliver scalable, secure, and innovative data-driven outcomes.

What You'll Do:

• Define end-to-end architecture for Data, Analytics, Machine Learning, AI, and Generative AI solutions
• Design data platforms, data lakes, data warehouses, and modern lakehouse architectures
• Architect batch and real-time data ingestion pipelines and ETL/ELT frameworks
• Design Generative AI applications using LLMs, RAG, vector databases, and prompt engineering
• Build and establish MLOps and LLMOps practices for deployment, monitoring, and governance
• Design cloud-native solutions on AWS, Azure, or Google Cloud, covering security, performance, and cost optimisation
• Engage stakeholders and present architecture solutions to executive and project teams

What We're Looking For:

• Bachelor's or master's degree in computer science, Information Technology, Data Science, or a related field
• 10+ years of IT experience with at least 3+ years in Solution Architecture
• Strong hands-on experience designing enterprise Data and AI solutions
• Proficiency with cloud platforms (AWS, Azure, or GCP) and associated managed services
• Experience with data technologies including Snowflake, Databricks, Azure Synapse, and Microsoft Fabric
• Hands-on knowledge of Python, SQL, Spark/PySpark, and DevOps/MLOps tooling (Docker, Kubernetes, Terraform, MLflow)

• Familiarity with Singapore Government technology standards, GCC environments, and GovTech governance frameworks is highly advantageous

What We Offer:

• Competitive salary
• Exposure to cutting-edge Data and AI technologies at enterprise scale
• Career progression opportunities within a growing technology consultancy
• Mentorship and knowledge-sharing with experienced technical leaders
• Collaborative and supportive team environment

How to Apply

Apply now with your latest CV or reach out to our recruitment team to learn more.

Role Overview:

We are looking for a Data Engineer to support large-scale government and defence-related data projects, focusing on building secure, scalable, and reliable data platforms and ETL/ELT pipelines across cloud and enterprise environments.

Job Responsibilities:

Data Engineering & Platform Development

• Design and develop scalable and reliable data pipelines.
• Build enterprise data platforms, including data warehouses, data lakes, and lakehouses.
• Implement cloud, hybrid, and on-premises data architectures aligned with enterprise standards.

ETL/ELT & Data Integration

• Lead ETL/ELT pipeline development, with Talend as a highly preferred platform.
• Integrate structured, semi-structured, and unstructured data sources.
• Implement and maintain data quality, validation, and error-handling frameworks.

Data Management & Governance

• Design and manage data storage solutions with a strong focus on object storage, data quality, and data governance.
• Implement and maintain data lifecycle management and cost-optimisation strategies.
• Ensure data lineage, traceability, and auditability.

Analytics & BI Enablement

• Engineer analytics-ready data models for reporting and self-service analytics.
• Enable BI dashboards, reports, and analytics through performant and governed data pipelines.

Security & Compliance

• Ensure compliance with government security and privacy requirements.
• Implement and maintain encryption, access controls, secure data handling practices, and system security policies.

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum 3 years of experience in enterprise data engineering roles.
• Strong hands-on data engineering experience.
• Strong SQL and Python skills.
• Experience with ETL/ELT tools, with Talend highly preferred.
• Experience with data warehouses, data lakehouses, data lakes, and object storage systems.
• Qlik Sense Enterprise integration experience is highly preferred.
• Prior CAT 1 / G50 security clearance is required.
• Previous experience delivering MINDEF projects is required.

1. Position Summary

We are looking for a Data Engineer to join our team and contribute to a major project within the semiconductor manufacturing domain. The role involves designing and implementing data pipelines, managing Oracle-based data environments, and supporting end-to-end BI processes — from data ingestion to visualization. This position is based on-site at our partner’s advanced manufacturing facility, offering hands-on exposure to large-scale industrial data systems.

2. Key Responsibilities

• Design, develop, and maintain Python-based applications and APIs to extract, transform, and deliver data in JSON format.
• Design and create robust data models to support efficient querying and reporting.
• Define relationships, hierarchies, and calculated columns/measures that align with business logic.
• Design, develop, and maintain data pipelines and ETL workflows for manufacturing data (ERP, MES, SPC, FDC, etc.).
• Implement and optimize database logic, including stored procedures, functions, and PL/SQL scripts.
• Build and manage staging schemas, data validation processes, and data transformation logic.
• Develop and maintain data marts and dimensional models to support analytics and reporting.
• Collaborate with BI developers and analysts to deliver Power BI dashboards, KPI reports, and visual analytics.
• Ensure data accuracy, consistency, and completeness across multiple source systems.
• Support data governance, documentation, and performance tuning efforts.
• Partner with internal and external stakeholders to ensure timely and high-quality data delivery for business use.
• Perform any ad-hoc duties assigned by the Company as and when required.

3. Qualifications& Skills

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• Minimum 3 years of experience in data engineering, data integration, or BI development.
• Proficient in Python programming, specifically for data extraction, API development, and JSON data manipulation.
• Strong understanding of data warehousing concepts, schema design, and ETL best practices.
• Solid working experience with relational databases (e.g. Oracle, SQL Server, MySQL, PostgreSQL), including stored procedures and query optimization.
• Proficient with ETL tools such as Pentaho Kettle, Informatica, Talend, or similar.
• Experience developing reports and dashboards in Power BI (or Tableau/Qlik).
• Familiarity with SQL pipelines, data validation, and data replication tools.
• Strong analytical and problem-solving mindset with attention to data quality and performance.
• Ability to work collaboratively with business, IT, and engineering teams in fast-paced environments.
• Excellent documentation and communication skills.

4. Preferred /Additional

• Experience in semiconductor or manufacturing systems (ERP, MES, SPC, FDC) preferred.
• Exposure to data replication frameworks (Oracle Golden Gate, SharePlex, AWS Glue) is an advantage.
• Experience developing custom Python applications/APIs for data extraction and familiarity with JSON data structures is highly preferred.
• Familiarity with cloud-based data warehouses (Snowflake, Redshift, Synapse) and Giga Report is a plus
• Knowledge of data governance frameworks, metadata management, and data security best practices.

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Data / ML Intern, BenefitBee

BenefitBee is a stealth-stage startup based in the US and Singapore, building AI-native infrastructure for the employee benefits world. The founding team has built and scaled venture-backed companies and brings operating experience from places like Wish, Meta, Blackrock and Mercer. If you join, you'll be learning directly from founders and operators who have done this at a serious scale.

Our vision
Employee benefits is a massive, deeply manual industry that still runs on PDFs, spreadsheets, and email. We think the entire workflow can be rebuilt around AI, turning messy, unstructured documents into structured intelligence that helps people make faster, better decisions. We're early and moving fast, and the people who join now will help shape both the product and the company.

What you'll work on

• Build Python pipelines to extract and clean unstructured text from insurance, medical, and academic documents

• Convert raw text into standardized schemas (JSON) that feed our downstream analytics

• Develop models to surface trends in claims, renewals, and preventative care outcomes

What we're looking for

• Pursuing or completed a degree in Data Science, CS, Math, Biomedical Engineering, or Bioinformatics

• Solid Python and a real grasp of evaluation metrics (Accuracy, AUC, F1, etc.)

• Hands-on experience parsing text from PDFs, spreadsheets, and other unstructured sources

• Bonus: you've wrangled genuinely ugly documents before and lived to tell the tale

You'll work directly with the founding team, ship things that go into the actual product, and see how an experienced team builds a company from zero.