Data Engineer
Posted
Summary
Data Engineer at TEKsystems (staffing firm) building batch and streaming data ingestion pipelines in Python for a key Financial Services client in Singapore. Day-to-day is hands-on ETL/ELT engineering, data quality checks, and production support using Python, SQL, Snowflake, AWS, and GitHub-based CI/CD in a hybrid, Agile squad.
- Strong hands on experience with Python for data engineering and pipeline development
- Proficiency in SQL and experience with large, structured datasets
- Exposure to Snowflake or similar cloud data warehouse platforms Overview We're hiring a Data Engineer to join a highly structured, enterprise‑grade technology environment undergoing a multi‑year data transformation initiative for one of our key Financial Services clients . You'll work within a modern, collaborative engineering squad responsible for building scalable data ingestion pipelines and enabling high‑quality, centralised data access across critical business domains. This role is ideal for someone who enjoys hands‑on engineering , data pipeline operations , and tackling real‑world production challenges in a mature environment with strong engineering standards. What You'll Do
- Design, develop, and maintain robust data ingestion pipelines (batch & streaming) using Python.
- Integrate data from APIs, file transfers, and relational databases (e.g., Oracle, MSSQL) into a cloud‑based data platform.
- Build and optimise ETL/ELT processes, ensuring reliability, scalability, and clean end‑to‑end data flow.
- Implement automated data quality checks, operational monitoring, and rerun/reprocessing capabilities.
- Work across the full SDLC: requirements, development, testing (SIT/UAT), deployment, and BAU support.
- Collaborate closely with data stewards, analysts, and cross‑functional stakeholders to deliver high‑quality outcomes.
- Participate in operational duties, including occasional low‑touch weekend support for deployment‑related issues.
- Uphold strong engineering discipline around compliance, documentation, version control, and CI/CD processes.
- Strong hands‑on experience with Python for data engineering and pipeline development.
- Proficiency in SQL and experience with large, structured datasets.
- Exposure to Snowflake or similar cloud data warehouse platforms.
- Experience with AWS services commonly used in data environments.
- Familiarity with CI/CD pipelines (e.g., GitHub).
- Strong understanding of data engineering fundamentals: ingestion patterns, orchestration, data lifecycle management.
- Ability to troubleshoot production issues independently with an operational mindset.
- Strong communication and collaboration skills within structured, cross‑team environments.
- Test‑driven development (TDD) or production‑grade coding practices.
- Experience with pipeline monitoring and observability tools.
- Background working in large, mature organisations with established governance frameworks.
- Prior exposure to enterprise‑scale data transformation or centralised data platform projects.
- You enjoy building and fixing pipelines end‑to‑end, not just writing scripts.
- You're comfortable working in environments where engineering hygiene, traceability, and compliance matter.
- You thrive in collaborative, mission‑driven teams with shared ownership.
- You're proactive, structured, and able to navigate complex data ecosystems confidently.
- You're open to light operational duty (very minimal weekend touchpoints during deployment cycles).
- You'll join a tight‑knit engineering squad working as one team.
- The wider group includes data management partners who support data quality, operations, and user engagement.
- Work is delivered in Agile sprints, with strong emphasis on communication and clear ownership.
- The culture is inclusive, supportive, and highly collaborative, with team members helping each other across development and operations.
- Hybrid work arrangement with rotational in‑office days depending on team schedule.
- Be part of a high‑impact, enterprise‑level data initiative that's central to organisational decision‑making.
- Enjoy the stability and structure of a large organisation while working in a modern, engineering‑driven team.
- Work on meaningful data domains with real operational importance and visibility.
- Opportunity to grow your cloud data engineering skills and gain exposure to end‑to‑end platform operations.
- The team invests heavily in mentoring, learning, and continuous improvement.
- Tech readiness is complete — you can make immediate impact from day one.