Senior Data Platform Engineer | Data Integration & Modernisation

NEXBRIDGE RECRUITMENT PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Nexbridge Recruitment Pte Ltd in Singapore seeks a Senior Data Engineer to lead architecture and implementation of ETL processes, data pipelines, and data integration from multiple sources. You will design scalable batch and real-time pipelines, ensure data quality, and mentor junior engineers.

The role requires strong Python and SQL skills, experience with CI/CD, Linux environments, and cloud platforms. You will collaborate with stakeholders to translate complex data requirements into robust

Qualifications

• 5 years of professional experience in data engineering, data platform development or a related software engineering role, with experience designing and implementing production-grade data solutions at scale.
• Strong proficiency in Python and SQL, with experience in complex data transformations, analysis and data quality monitoring.
• Strong experience in batch processing, ETL, data integration and data pipeline architecture.
• Strong working knowledge of Linux/Unix environments, shell scripting and command-line tools for data processing.
• Strong understanding and practical application of software engineering practices, including modular design, configuration management, logging, exception handling, testing and technical documentation.
• Experience defining or applying engineering standards for production systems.
• Experience designing technical solutions and making engineering trade-off decisions involving performance, maintainability, scalability and operational reliability.
• Experience leading or providing technical guidance for data pipeline development, system migration or modernisation initiatives.
• Experience conducting code reviews and mentoring or providing technical guidance to other engineers.
• Experience with version control using Git, including branching strategies, merge requests, code reviews and CI/CD pipelines for automated testing and deployment.
• Experience with cloud platforms and orchestration or CI/CD tools is preferred.
• Strong problem-solving, analytical and communication skills, with the ability to work independently and provide technical leadership when resolving complex engineering problems.

Responsibilities

• Lead the architecture, design and implementation of ETL processes, workflows and data pipelines for ingestion, transformation and integration of data from multiple source agencies.
• Build and maintain large-scale batch and real-time data pipelines, including dependency management, failure handling, recovery and operational monitoring.
• Develop and maintain modular, production-quality code for statistical production processes, including modernisation of legacy processes while preserving business logic.
• Review complex business logic and provide technical direction for data migration and modernisation initiatives.
• Lead database and data model design, including schema design, storage patterns and performance optimisation for large-scale statistical datasets.
• Design and drive the adoption of reusable data engineering components and standards to streamline production workflows.
• Design and implement CI/CD pipelines for data engineering workflows to automate testing and deployment across Development, UAT and Production environments.
• Establish version control structures using GitLab, including branching strategies, merge requests and code review frameworks.
• Provide technical reviews for solution designs, merge requests and implementation approaches, and promote engineering standards across the team.
• Troubleshoot production incidents, monitor pipeline health and optimise system performance for large-scale datasets.

Skills

Data engineering

Python

SQL

Troubleshooting

Communication

Mentoring

Tools

Git

GitLab

CI/CD

Linux

Shell scripting

Job description

Job Responsibilities

• Lead the architecture, design and implementation of ETL processes, workflows and data pipelines for the ingestion, transformation and integration of data from multiple source agencies.
• Build and maintain efficient and reliable large-scale batch and real-time data pipelines, including dependency management, failure handling, recovery and operational monitoring.
• Develop and maintain modular, production-quality code for statistical production processes, including the modernisation of legacy processes while preserving existing business logic and reconciling outputs against current production results.
• Review complex business logic and provide technical direction for data migration and modernisation initiatives.
• Lead database and data model design, including schema design, storage patterns and performance optimisation for large-scale statistical datasets.
• Design and drive the adoption of reusable data engineering components, including common libraries, configuration frameworks, logging standards and utilities to streamline production workflows and promote consistent engineering practices.
• Design and implement CI/CD pipelines for data engineering workflows to automate testing and deployment, while establishing workflows across Development, UAT and Production environments.
• Lead the design and configuration of complex pipeline workflows and schedules using enterprise tools, including dependency management, failure handling, recovery and operational monitoring.
• Establish version control structures using GitLab, including branching strategies, merge requests and code review frameworks, while maintaining technical architecture and implementation documentation.
• Provide technical reviews for solution designs, merge requests and implementation approaches, and promote appropriate engineering standards across the development team.
• Troubleshoot production incidents, monitor pipeline health and continuously optimise system performance for large-scale datasets.
• Lead investigations into complex production issues, identify root causes and implement preventive measures and performance improvements.
• Provide technical guidance and mentoring to data engineers on coding practices, solution design, troubleshooting and implementation decisions.
• Collaborate with technical teams, business users and stakeholders to translate complex business and statistical processing requirements into robust technical solutions.
• Identify technical risks, dependencies and improvement opportunities, and recommend appropriate design and implementation approaches.

Job Requirements

• 5 years of professional experience in data engineering, data platform development or a related software engineering role, with experience designing and implementing production-grade data solutions at scale.
• Strong proficiency in Python and SQL, with experience in complex data transformations, analysis and data quality monitoring.
• Strong experience in batch processing, ETL, data integration and data pipeline architecture.
• Strong working knowledge of Linux/Unix environments, shell scripting and command-line tools for data processing.
• Strong understanding and practical application of software engineering practices, including modular design, configuration management, logging, exception handling, testing and technical documentation.
• Experience defining or applying engineering standards for production systems.
• Experience designing technical solutions and making engineering trade-off decisions involving performance, maintainability, scalability and operational reliability.
• Experience leading or providing technical guidance for data pipeline development, system migration or modernisation initiatives.
• Experience conducting code reviews and mentoring or providing technical guidance to other engineers.
• Experience with version control using Git, including branching strategies, merge requests, code reviews and CI/CD pipelines for automated testing and deployment.
• Experience with cloud platforms and orchestration or CI/CD tools is preferred.
• Strong problem-solving, analytical and communication skills, with the ability to work independently and provide technical leadership when resolving complex engineering problems.

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