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

StrongSQL 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.