Senior Data Engineer - Python/ETL/Databricks/SQL

  • Hamilton Barnes
  • 29/04/2026
Contractor Information Technology Telecommunications SQL Oracle Python Testing

Job Description

Senior Data Engineer - Python/ETL/Databricks/SQL

Location: London (Canary Wharf) - Hybrid (3 days onsite)
Rate: £425 - 450 per day (Inside IR35)
Contract: 6 months
Start: ASAP

The Role

We are seeking an experienced Senior Data Engineer to join a large-scale enterprise programme within the financial services sector. This is a hands-on, delivery-focused role centred on designing and building scalable ETL/ELT pipelines, supporting business-critical data platforms, and ensuring high standards of data quality, reliability, and performance. You will work closely with business and technology stakeholders to translate requirements into robust, production-ready data solutions.

Key Responsibilities

  • Design, build, and maintain scalable ETL/ELT data pipelines
  • Develop and optimise data models and data architecture
  • Implement data processing solutions using Python and SQL
  • Analyse existing data flows and propose improvements to architecture and performance
  • Support data validation, testing, and quality frameworks
  • Troubleshoot and resolve data-related production issues
  • Collaborate with cross-functional teams including Technology, QA, and Operations
  • Support integration of data pipelines across multiple systems and platforms
  • Contribute to Agile delivery, including sprint planning and backlog refinement
  • Ensure adherence to data governance, controls, and compliance standards

Must-Have Experience

  • Strong hands-on experience as a Data Engineer
  • Proven experience building ETL/ELT pipelines end-to-end
  • Strong Python skills (data processing/pipeline development)
  • Experience with at least one major database (PostgreSQL, BigQuery, or Oracle)
  • Solid data modelling experience (schema design, performance optimisation)
  • Experience working with production data systems and resolving issues
  • Strong understanding of data engineering concepts and best practices
  • Experience working in Agile environments