Total 963 data entry job vacancies in Information Technology category

Responsibilities:

• Design, develop, and maintain robust ETL/ELT pipelines for structured and unstructured data.

• Design and develop data products to support business decision making.
• Solve complex problems using analytical, statistical and machine learning approaches.
• Optimize data architectures such as data lakes, warehouses, and streaming systems to improve performance, scalability and platform stability.
• Collaborate with stakeholders to understand data requirements and translate them into technical solutions.
• Develop automated processes and frameworks to address recurring business questions.
• Ensure data governance, security and best practices are followed.

Requirements:

• Bachelor's degree or above in Statistics, Applied Mathematics, Computer Science or a related field.
• 2+ years of working experience in data engineering or a related role; Fresh graduates with relevant internship experiences are encouraged to apply.
• Strong proficiency in programming languages such as Java, Python and SQL.
• Hands-on experience in real-time data processing tools and streaming technologies (Spark, Flink, Kafka etc).
• Strong analytical and problem-solving skills.

Preferred:

• Basic understanding of machine learning concepts (e.g., classification, regression, clustering, neural networks etc).
• Familiarity with SQL and NoSQL databases.
• Experience building data products using cloud platforms and data warehousing solutions such as AWS and AliCloud.

The Data Engineer is responsible fordesigning, building, and maintaining data infrastructure that supportsanalytics, applications, and enterprise reporting needs. This includesconstructing scalable pipelines, managing data flows across systems, andenabling reliable storage, integration, and retrieval of information acrosscloud and on‑premise environments. The role involves close collaboration withcross‑functional teams to deliver data‑driven solutions that are robust, secure,and high-performing.

Key Responsibilities

1. Data Architecture & Development

• Design, create, and deploy data models, tables, views, and data marts across data warehouses, operational data stores, data lakes, and data virtualization environments.
• Build backend APIs and database structures to support applications and data products.

2. Data Extraction & Transformation

• Perform data extraction, cleansing, transformation, and blending across multiple sources.
• Conduct web scraping activities when needed, using appropriate automation tools.
• Ensure data reliability, accuracy, and consistency through well-structured data processing workflows.

3. Data Pipelines & Processing

• Develop and maintain large-scale batch and real-time data pipelines using modern data engineering frameworks.
• Implement ETL/ELT processes leveraging tools such as SSIS, AWS Glue, AWS DMS, Python, Lambda, ECS tasks, EventBridge, Spring, or similar technologies.
• Integrate data from distributed systems and eliminate data silos through scalable and secure data flows.

4. Collaboration & Product Delivery

• Partner with Project Managers, Data Architects, Business Analysts, Frontend Developers, Designers, and Data Analysts to deliver end-to-end data-driven solutions.
• Participate in Agile ceremonies and contribute to continuous integration and delivery practices.
• Engage in pair programming and participate in code reviews to ensure coding standards and quality.

5. Infrastructure, Cloud & Big Data

• Work with cloud platforms such as AWS, Azure, or Google Cloud to build and operate cloud-native data solutions.
• Design and manage data pipelines in big data environments using tools like Spark, Hadoop, Kafka, RabbitMQ, or similar technologies.
• Ensure systems are resilient, scalable, and suitable for production workloads.

6. Data Governance & Security

• Apply data governance principles, ensuring compliant access, secure storage, and proper data handling practices.
• Implement security best practices for data assets and support policy enforcement across systems.

Required Technical Skills

Data Processing & Programming

• Proficient in data cleaning and transformation using SQL, Python (pandas), R, or equivalent tools.
• Strong skills in ETL/ELT pipeline development and workflow orchestration.

Databases & Storage

• Hands-on experience designing and operating relational and non-relational databases such as SQL Server, PostgreSQL, MySQL, MongoDB, Cassandra, Athena, SQLite, VoltDB, or S3-based storage.
• Familiarity with data warehouse, data lake, data mart, and data virtualization concepts.

System Design & APIs

• Solid understanding of system design, data structures, algorithms, and backend development.
• Comfortable working with REST APIs, HTTP protocols, and integrating various data sources.

Big Data & Distributed Systems

• Knowledge of distributed systems and tools (Hadoop, Spark, Kafka, etc.).
• Ability to implement streaming, micro‑batch, or batch processing pipelines.

Web Scraping & Automation

• Experience with web scraping technologies like BeautifulSoup, Selenium, CasperJS, PhantomJS, Node.js, or similar tools.

Security & Data Governance

• Familiar with access control, encryption, audit logging, and other data security practices.

Tools & Environment

• Comfortable working in both Windows and Linux environments.
• Experience using CI/CD pipelines and participating in DevOps-oriented workflows.

Soft Skills & Attributes

• Detail‑oriented with a strong focus on problem solving and analytical thinking.
• Good communication skills, capable of discussing technical topics with both technical and non‑technical stakeholders.
• Collaborative mindset and ability to work as a bridge between engineering and analytics teams.
• Self‑motivated, adaptable, and comfortable managing work in a fast-paced Agile environment.

Please submit resumes to john@oaktree.com.sg with the following details in MS Word format:

- Position applying for

- Current remuneration

- Expected remuneration

- Notice period

John Goh Meng Chye

EA License No : 06C4642

EA Reg No : R1102621

We regret that only shortlisted candidates will be notified.

We are looking for a detail-oriented Data Entry Administrator to support daily administrative and data management tasks. The role involves accurate data input, record keeping, and assisting with general office operations.

• Answer phone calls.
• Enter, update, and maintain data in systems and database
• Verify accuracy of data and correct any errors
• Prepare, sort, and organize documents for data entry
• Maintain proper filing (physical and digital records
• Generate basic reports when required
• Assist with administrative tasks (emails, printing, scanning, etc.)
• Ensure confidentiality of sensitive information
• Any other ad hoc duties assigned.

At EY, we develop you with future-focused skills and equip you with world-class experiences. We empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams.

We work together across our full spectrum of services and skills powered by technology and AI, so that business, people and the planet can thrive together.

We’re all in, are you?

Join EY and shape your future with confidence.

About the opportunity

EY AI & Data is the data and advanced analytics capability within EY Asia-Pacific, with over 500 specialist employees working across multiple industry sectors. We implement information-driven strategies, data platforms and advanced data analytics solution systems that help grow, optimize and protect client organizations. We go beyond strategy and provide end to end design, build and implementation of real-life data environments and have some of the best architects, project managers, business analysts, data scientists, big data engineers, developers and consultants in the region. We are looking for a Data Analyst within the AI & Data team in our Singapore office. This role is offered on a flexible full-time basis.

Your key responsibilities:

• Collaborate with cross-functional teams to gather requirements, define data-related technical issues, and provide solutions.
• Create informative and interactive dashboards and reports in Power BI, Qlik or similar tools to meet the needs of the business.
• Write advanced SQL queries for data manipulation and retrieval from relational databases.
• Develop and optimize data models within the dashboarding tool for reporting and analytics.
• Perform data extraction, transformation, and loading of large and complex data sets from various source systems.
• Ensure data quality and integrity by implementing data validation and testing within ETL processes.
• Monitor ETL jobs, troubleshoot any issues, and perform performance tuning to improve data processing.
• Stay current with the latest technologies and best practices in data engineering and business intelligence

Skills & attributes for success:

• Experience of data-driven organizational transformation supported by data insights and good story telling
• Experience in business intelligence, data warehousing/platform, or data strategy projects
• Experience in ETL development and Data Analysis
• Knowledge and experience in data governance, data security, and privacy practices
• Exceptional communication, documentation and presentation skills and stakeholder management experiences

To qualify for the role, you must have

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Minimum of 5 year of experience as a Data Analyst with experience in ETL development and data warehousing.
• Prior experience with Azure Data Factory, including building and optimizing data pipelines, is preferred.
• Strong proficiency in writing and optimizing SQL queries.
• Expertise in popular commercial BI tools, such as Power BI, Qlik.
• Familiarity with data governance, data security, and privacy practices.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills to work effectively with both technical and non-technical team members.

Ideally, you’ll also have

• Dashboarding experience with Power BI, Qlik or equivalent tools
• Experience in engaging with both technical and non-technical stakeholders
• Consulting/Professional Services experience and background, including engaging directly with clients

What we look for

• Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry.
• An effective communicator, you’ll be a confident leader equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization.

What we look for

Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry. An effective communicator, you’ll be a confident team player that collaborates with people from various teams while looking to develop your career in a dynamic organization.

What working at EY offers

EY offers a competitive remuneration package where you’ll be rewarded for your individual and team performance. We are committed to being an inclusive employer and are happy to consider flexible working arrangements. Plus, we offer:

• Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next.
• Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
• Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs.
• Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.

Company description

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

All in to shape the future with confidence.

Roles & Responsibilities

Responsibilities

·      Perform duty and/or shift duty roster to manage data centre (DC) operations, maintenance, troubleshooting, project rollout and facilities related matters. This includes maintain and repair of infrastructure systems and all critical facilities equipment including the monitoring of BMS System

·      Perform DC monitoring and maintenance on infrastructure systems, critical facilities and associated equipment.

·      Perform preventive and corrective support to scheduled or unscheduled maintenance on DC infrastructure systems, critical facilities equipment and/or services.

·      Ensure all subcontractors deliver a quality and competent service and all contractual obligations are met. Supervise the vendors to all scheduled and adhoc activities related to DC facilities.

·      Perform DC and critical facilities work on environmental and management programs

·      Perform equipment functionality test and data analysis

·      Perform assets management duty, including maintaining of inventory, change and control programs and purchase of parts and supplies

·      Promptly respond and attend to incident and/or emergency situations

·      Provide standby support upon activation for shift duty stand-in and/or other coverage

·      Conduct routine, sanity check and ongoing assessment of DC infrastructure systems and critical facilities operations

Requirements

·      Degree or Diploma in Electrical/Mechanical/Building Services Engineering or equivalent

·      At least 2 years’ experience in facilities operations experience in DC or 24/7 critical environment management.

·      Detailed understanding and experience of the electrical and mechanical systems used in a DC and commercial environment.

·      Experience in vendor management, ability to manage and progress monitoring to ensure objectives are achieve for outsourced support and projects.

Role Description

• You are operating Global Data Platform components (VM Servers, Kubernetes, Kafka) and applications (Apache Stack, Collibra, Databricks and similar).
• Implement automation of infrastructure, security components, and Continuous Integration & Continuous Delivery (CI/CD) for optimal execution of data pipelines (ELT/ETL).
• Develop solutions to build resiliency in data pipelines that perform health checks, monitoring, and alerting mechanisms; quality, timeliness, recency, and accuracy of the data delivery are improved.
• Apply DevSecOps and Agile approaches to deliver a holistic and integrated solution in iterative increments.
• Liaison and collaborate with enterprise security, digital engineering, and cloud operations architecture solution frameworks to drive consensus on design.
• Review system issues, incidents, and alerts to identify root causes and continuously implement features to improve platform performance.
• Be current on the latest industry developments and technology trends to effectively lead and design new features and capabilities.

Experience

• You have 5+ years of experience in building or designing large‑scale, fault‑tolerant, distributed systems.
• Migration experience of storage technologies (e.g. HDFS to S3 Object Storage).
• Integration of streaming and file‑based data ingestion/consumption (Kafka, Control‑M, AWS).
• Experience in DevOps, data pipeline development, and automation using Jenkins, Ansible, Chef, XL Release, and XL Deploy.
• Experience predominantly with on‑prem Big Data architecture; cloud migration experience is welcome.
• Hands‑on experience integrating Data Science Workbench platforms (e.g. Datiku).
• Experience with Agile project management methods (e.g. Scrum, SAFe).
• Supporting analytical value streams from enterprise reporting (e.g. Tableau) to data science (incl. ML Ops).

Skills

• Hands‑on working knowledge of large data solutions (e.g. data lakes, delta lakes, data meshes, data lakehouses, data platforms, data streaming solutions).
• In‑depth knowledge and experience in one or more large‑scale distributed technologies, including but not limited to:
• Hadoop ecosystem
• Kafka
• Kubernetes
• Spark
• Expert in Python and Java or another programming language (Scala/R, Linux/Unix scripting).
• VM setup and scaling (K8s scaling, managing Docker with Harbor, pushing images through CI/CD).
• Experience using data formats such as Apache Parquet, ORC, Avro.
• Exposure to machine learning algorithms is a plus.
• Good knowledge of German is beneficial; excellent command of English is essential.
• Knowledge of the financial sector and its products.

· 8+ years of data engineering experience, preferably in financial services or high-volume data environments

· Advanced SQL Server expertise, including:

o    Query optimization, execution plan analysis, and performance tuning

o    Index design, maintenance, and partitioning strategies for large tables

o    Deadlock analysis, resolution, and troubleshooting

o    Database design, normalization, and experience managing large-scale databases (multi-TB environments)

· Solid understanding of data engineering principles: data modeling, ETL best practices, and data quality frameworks

· Java/J2EE development skills for building scalable data applications

· Good to have the proficiency with Apache Spark (DataFrames, RDDs, Spark SQL) forbuilding and optimizing production-grade ETL pipelines that handle large-scale distributed data processing

Job Summary:

We are seeking a highly skilled Big Data Platform Engineer to design, build, and operate large-scale, distributed data platforms. This role is responsible for ensuring the reliability, scalability, and performance of enterprise data systems, while driving automation, DevSecOps practices, and continuous improvement across data pipelines and platform infrastructure.

You will work closely with cross-functional teams to deliver robust, secure, and high-performing data solutions that support enterprise reporting, analytics, and data science initiatives.

Job Responsibilities:

• You are operating Global Data Platform components (VM Servers, Kubernetes, Kafka) and applications (Apache stack, Collibra, Dataiku and similar)
• Implement automation of infrastructure, security components, and Continuous Integration & Continuous Delivery for optimal execution of data pipelines(ETL/ELT)
• Develop solutions to build resiliency in data pipelines with platform health checks, monitoring, and alerting mechanisms, quality, timeliness, recency, and accuracy of data delivery are improved
• Apply DevSecOps & Agile approaches to deliver the holistic and integrated solution in iterative increments
• Liaison and collaborate with enterprise security, digital engineering, and cloud operations to gain consensus on architecture solution frameworks
• Review system issues, incidents, and alerts to identify root causes and continuously implement features to improve platform performance
• Be current on the latest industry developments and technology trends to effectively lead and design new features / capabilities

Job Requirements:

• 5+ years of experience in building or designing large-scale, fault-tolerant, distributed systems
• Migration experience of storage technologies (e.g. HDFS to S3 Object Storage)
• Integration of streaming and file-based data ingestion / consumption (Kafka, Control M, AWA)
• Experience in DevOps, data pipeline development, and automation using Jenkins and Octopus (optional: Ansible, Chef, XL Release, and XL Deploy)
• Experience predominately with on-prem Big Data architecture, cloud migration experience might come handy
• Hands-on experience in integrating Data Science Workbench platforms (e.g. Dataiku)
• Experience of agile project management and methods (e.g. Scrum, SAFe)
• Supporting all analytical value streams from enterprise reporting (e.g. Tableau) to data science (incl. ML Ops)
• Hands-on working knowledge of large data solutions (for example: data lakes, delta lakes, data meshes, data lakehouses, data platforms, data streaming solutions.)
• In-depth knowledge and experience in one of more large scale distributed technologies including but not limited to: Hadoop ecosystem, Kafka, Kubernetes, Spark
• Expert in Python and Java or another static language like Scala/R, Linux/Unix scripting, Jinja templates, puppet scripts, firewall config rules setup
• VM setup and scaling (pods), K8S scaling, managing Docker with Harbor, pushing images through CI/CD
• Experience using data formats such as Apache Parquet, ORC or Avro Experience in machine learning algorithms is a plus.
• Good knowledge of German is beneficial, excellent command of English is essential
• Knowledge of financial sector and its products

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

Role Summary

We are seeking a highly capable Data Center Engineer to support both data center construction and infrastructure operations. This role is instrumental in delivering data center build-out projects from design review through installation, testing, commissioning, and final handover, while ensuring stable and reliable day-to-day operations after project completion.

The successful candidate will actively participate in project construction phases, system installation, testing and commissioning, and will subsequently transition into ongoing operational support following project completion. The ideal candidate will have hands-on experience in mission-critical environments and a solid understanding of electrical and mechanical systems within data centers.

This position requires close collaboration with contractors, vendors, consultants, and internal stakeholders to ensure projects are delivered safely, on schedule, and in accordance with technical specifications and industry standards. The role demands strong technical judgment, hands-on execution capability, and the ability to manage complex mission-critical infrastructure systems in high-availability environments.

Key Responsibilities

Data Center Construction & Build-Out

·       Support data center new build and expansion projects from design phase to handover.

·       Review engineering drawings, MEP layouts, rack layout plans, and power distribution design.

·       Participate in site surveys, design review meetings, and technical clarification discussions.

·       Supervise installation of:

• Electrical systems (UPS, switchgear, PDU, ATS, power cabling)

•  Mechanical systems (chillers CRAC/CRAH, pumps, piping, cooling towers)

•   Structured cabling and fiber infrastructure

·       Coordinate with contractors to ensure installation complies with design specifications and industry standards.

·       Support factory acceptance test (FAT), site acceptance test (SAT), and commissioning activities.

·       Identify installation defects and track punch list items to closure.

Infrastructure Operations

·       Monitor and maintain power systems, cooling systems, and environmental controls.

·       Perform troubleshooting for electrical, mechanical, and infrastructure-related issues.

·       Respond to system alarms and incidents in a timely manner.

·       Support preventive maintenance and corrective maintenance activities.

Power & Capacity Management

·       Monitor load capacity of UPS, generators, PDUs, and distribution panels.

·       Validate rack power provisioning and load balancing.

·       Review and optimize power utilization efficiency.

·       Track capacity planning for power and cooling resources.

Documentation & Reporting

·       Maintain as-built drawings and infrastructure documentation.

·       Update rack layout, cable routing diagrams, and electrical single-line diagrams.

·       Track asset inventory and installation status.

·       Prepare construction progress reports and commissioning reports.

Vendor & Project Coordination

·       Coordinate with contractors, consultants, and equipment vendors.

·       Attend project meetings and technical workshops.

·       Review technical submittals and installation method statements.

·       Support project schedule tracking and risk mitigation.

Required Qualifications

• Bachelor’s degree in electrical engineering, Mechanical Engineering, Construction Engineering, or related field.
  
• 3–5years of experience in data center construction or critical facility environment.
  
• Strong knowledge of:
  
  - Power distribution systems
  - UPS / Generator systems
  - Cooling systems
  - Structured cabling
  - Commissioning process
  
• Experience in site supervision and contractor coordination.
  
• Ability to read and interpret MEP drawings and technical documentation.
  
• Willingness to travel as required to support project site oversight and operational activities.

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

Key Responsibilities

• Build and manage scalable big data platforms and pipelines (ETL/ELT)
• Implement automation and CI/CD for data and infrastructure
• Develop streaming and batch data solutions using Kafka & Spark
• Ensure platform reliability through monitoring and performance tuning
• Collaborate with cross-functional teams using Agile & DevSecOps practices

Mandatory Skills

• Hadoop, Spark, Kafka
• Strong experience in DevOps & CI/CD
• Experience with distributed systems and data pipelines
• Proficiency in Python / Java / Scala
• Linux/Unix environment experience
  
  Preferred Skills
• Kubernetes, Docker, Cloud (AWS/Azure/GCP)
• Data formats: Parquet, ORC, Avro

Tools: Ansible, Jenkins

Exposure to Dataiku / ML Ops is a plus

• Education
• Bachelor’s degree in Computer Science or related field

What you will be working on

The successful candidate shall be responsible, among others, to:

• Analyse, correlate, interpret and visualise data to uncover trends and patterns.
• Formulate and test threat hunting hypothesis.
• Produce insights and supporting evidence to support decision making.
• Compile and share intel with counterparts for prompt intervention actions.
• Translate concepts and results into reports and presentation for senior stakeholders

What we are looking for

• Background in Computer Science / Computer Engineering / Mathematics / Statistics / Data Science and Analytics or equivalent.
• Knowledge of cybersecurity concepts and applications. Candidates with relevant cybersecurity certifications are preferred.
• At least 3 year of experience in data transformation, interpretation, and quantitative data analysis.
• Knowledge of statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with their application is preferred.
• Experience in using databases and frameworks for big data analytics such as Hadoop / Hive / Spark, and able to write complex SQL queries.
• Domain knowledge and experience in Computer Networking, Network Security, or System Security is preferred.
• Fast learner with self-motivation and independence to acquire knowledge on new domains or technologies quickly.

Data engineer (Azure) – Synapse and Pyspark, Python, Datawarehouse and Azure Data Explorer, Azure Devops

Job Scope

• Design, review and development of Pyspark scripts. Testing, troubleshooting of data pipelines, orchestration.

• Designing and developing reports and dashboards in PowerBI,setting up access control with row level security DAX query experience.

• Establishing connections to source data systems such as on-prem databases, IOT devices, APIs.

• Managing the collected data in appropriate storage/data-base solutions e.g. file systems, SQL servers, Big Data platforms such as Hadoop, HANA, etc. as required by the specific project requirements.

• Design, development of relevant data pipelines using pyspark, copy data activities for batch ingestion.

• Performing data integration e.g. using database table joins, or other mechanisms at an appropriate level as required by the analysis requirements of the project.

• Deployment of pipeline artifacts from one environment to the other using Azure Devops.

Skills & Experience

• Bachelor’s Degree in Computer Science or Engineering with 2 years of experience in Azure Data engineering, Python, Pyspark or Big Data development.

• Sound Knowledge of Azure Synapse analytics for pipelines, orchestration, set up.

• 1-2 experience in Visualization design and development with Power BI. Knowledge on row-level security, access control.

• Sound experience in SQL, Datawarehouse, data marts, data ingestion with Pyspark and Python.

• Expertise in developing and maintaining ETL processing pipelines in cloud-based platforms such as AWS, Azure, etc. (Azure Synapse or data factory preferred)

• Team player with good interpersonal, communication, and problem-solving skills.

• Preferred to have Devops expertise.

Working hours :

8:30am to 6pm (Monday to Friday) onsite, no hybrid option.

Responsibilities:

• Lead and advise agencies on data engineering strategy, architecture, and implementation aligned with the Digital Government Blueprint (DGB2.0).
• Translate business data requirements into technical specifications and scalable solutions.
• Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from diverse sources.
• Design and implement secure, cloud-based data infrastructure and access mechanisms.
• Monitor and optimize ETL systems and databases for performance, reliability, and scalability

Requirement:

• 10+ years of experience in data engineering, cloud infrastructure, or platform engineering.
• Deep understanding of system design, data structures, algorithms, and data modeling.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and distributed data technologies (Spark, Hadoop).
• Proficiency in Python, Java, Scala, and SQL.
• Experience with orchestration frameworks (Airflow, Azure Data Factory) and DevOps tools(Docker, Git, Terraform).
• Familiarity with CI/CD pipelines and infrastructure-as-code practices.
• Experience with Databricks and implementing batch/real-time data pipelines.

Interested applicants, Please send your updated resume in Word format to hres@itcspl.com

Please indicate Job Code "Data Engineer - 101" on email subject

We regret that only shortlisted candidates will be notified.

Bacalso John Bryan Bedayo (Reg No. R1106648)

IT Consultancy & Services Pte Ltd

EA No: 92C5311

Please visit www.itcspl.com to learn more information about ITC