Data Engineer

Design enterprise data models across a large-scale Data Hub platform, sitting at the intersection of architecture, analysis, and delivery.

You'll translate business requirements into conceptual, logical, and physical data models across Data Lake, Kimball, and Data Vault patterns. Day-to-day you're producing source-to-target mapping documents, running data profiling and discovery, designing interfaces between source and target systems, and supporting development and QA teams through implementation and performance tuning.

This is a contract role embedded in a Platform Engineering team that works across a genuinely complex enterprise data environment. You'll be working with EA Sparx for modelling, SQL at an advanced level, and BI tools including Tableau and MicroStrategy. The team also has desirable use of Python, PySpark, and AWS services including Sagemaker, so if you've got that background it'll be useful.

You won't be working in isolation. The role connects directly with a Data Platform Architect, Data Solutions Lead, Business Analysis and Reporting teams, and delivery managers. That means your designs need to be clearly documented and communicated, not just technically sound. You'll be expected to push back on business requirements where data quality or security considerations haven't been properly thought through.

What You'll Do

• Design data solutions across Big Data and Enterprise Data Warehouse platforms, including source-to-target mapping and interface design.
• Build conceptual, logical, and physical data models using EA Sparx across Data Lake, Kimball, and Business Feature modelling techniques.
• Run data profiling, discovery, and proof-of-concepts to validate designs before development begins.
• Work across architecture, development, and QA teams to ensure designs are implemented correctly and performance issues are addressed early.

What You'll Need

• Advanced SQL and hands-on experience with data modelling tools, specifically EA Sparx and ideally ERWIN.
• Solid data modelling across at least one of Data Lake, Kimball, Data Vault, or Data Mart patterns.
• Experience with BI tools such as Tableau or MicroStrategy, and a working knowledge of cloud data technologies.
• Python, PySpark, or AWS data platform experience is a genuine advantage.

About the Company

They're a large organisation running a mature enterprise data platform with significant investment in cloud and big data capability. The team is technically focused and delivery-oriented, working on initiatives that span the full data lifecycle from ingestion through to reporting and analytics.

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