- 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, enterprisegrade technology environment undergoing a multiyear 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 highquality, centralised data access across critical business domains.
This role is ideal for someone who enjoys
handson engineering,
data pipeline operations, and
tackling realworld 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 cloudbased data platform.
- Build and optimise ETL/ELT processes, ensuring reliability, scalability, and clean endtoend 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 crossfunctional stakeholders to deliver highquality outcomes.
- Participate in operational duties, including occasional lowtouch weekend support for deploymentrelated issues.
- Uphold strong engineering discipline around compliance, documentation, version control, and CI/CD processes.
What You'll Bring
MustHave Skills
- Strong handson 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, crossteam environments.
NicetoHave Skills
- Testdriven development (TDD) or productiongrade coding practices.
- Experience with pipeline monitoring and observability tools.
- Background working in large, mature organisations with established governance frameworks.
- Prior exposure to enterprisescale data transformation or centralised data platform projects.
Who You Are
- You enjoy building and fixing pipelines endtoend, not just writing scripts.
- You're comfortable working in environments where engineering hygiene, traceability, and compliance matter.
- You thrive in collaborative, missiondriven 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).
Team & Ways of Working
- You'll join a tightknit 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 inoffice days depending on team schedule.
Why This Role Is Appealing
- Be part of a highimpact, enterpriselevel data initiative that's central to organisational decisionmaking.
- Enjoy the stability and structure of a large organisation while working in a modern, engineeringdriven team.
- Work on meaningful data domains with real operational importance and visibility.
- Opportunity to grow your cloud data engineering skills and gain exposure to endtoend platform operations.
- The team invests heavily in mentoring, learning, and continuous improvement.
- Tech readiness is complete you can make immediate impact from day one.
We regret to inform that only shortlisted candidates will be notified.
EA registration number:
ANDREW JONAS MATTHEW, R21103843
Allegis Group Singapore Pte Ltd, Company Reg No. 200909448N, EA Licence No. 10C4544
