Data Engineer

We’re looking for a Data Engineer  with strong core data-engineering fundamentals to help us build and strengthen the data infrastructure supporting our analytics, reporting, and digital financial services.

You don’t need to come in knowing every platform or technology in our environment. What matters most is a solid foundation in data engineering, hands-on problem-solving skills, and the ability to learn and work with new technologies.

What You’ll Do

• Build, maintain, and optimize ETL/ELT data pipelines

• Work with relational databases and develop efficient SQL queries

• Support data warehousing, data modeling, and data-quality initiatives

• Investigate pipeline failures, reconcile data discrepancies, and perform root-cause analysis

• Use Python for data processing and automation

• Help ensure data accuracy, reliability, and availability for reporting and analytics

• Maintain clear technical documentation and support data lineage and metadata requirements

• Collaborate with technical teams and business stakeholders in delivering reliable data solutions

• Work within version-control and development practices for data solutions

What We’re Looking For

✓ At least 3 years of relevant experience  in Data Engineering, database development, or a similar role

✓ Strong   SQL skills , including query optimization and relational databases

✓ Practical experience building and maintaining  ETL/ELT pipelines

✓ Working knowledge of Python  for data processing and automation

✓ Good understanding of  data warehousing, data modeling, and data-quality principles

✓ Experience troubleshooting data-pipeline failures and reconciling data discrepancies

✓ Familiarity with Git or other version-control tools

✓ Good communication and documentation skills, with the ability to work with both technical and business stakeholders

An Advantage, But Not Required

• Microsoft Fabric, Azure Data Factory, or similar cloud data platforms
• PySpark, Apache Spark, or distributed data processing
• Kafka, event streaming, or near-real-time data pipelines
• Lakehouse architecture
• CI/CD and DevOps practices for data pipelines
• Data governance, lineage, metadata management, and access controls
• Banking, payments, fintech, or other financial services experience

Don’t tick every box?

If you have strong Data Engineering fundamentals and the ability to learn new technologies, we still encourage you to apply. Platform-specific tools in our environment can be learned on the job.

Interested?

Apply through LinkedIn and tell us about the data solutions you’ve worked on.