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Senior Data Engineer
Contract - initial 3 months
Onsite in London 5 days per week at Customer
The ideal candidate blends strong commercial acumen and consulting chops with hands-on technical execution—specifically leveraging the Databricks Data Intelligence Platform to solve complex enterprise data challenges.
Key Responsibilities
- Technical Leadership & Consulting: Partner with key client stakeholders (CDOs, Lead Architects, Enterprise Data Teams) to translate complex business requirements into scalable, modern data solutions.
- Databricks Solution Architecture: Design, build, and optimize enterprise data pipelines, lakehouses, and analytics platforms utilizing the Databricks unified analytics stack.
- Project Delivery: Take hands-on ownership of technical deliverables across the entire software development lifecycle (SDLC)—from discovery, proof-of-concept (PoC), and design to deployment, performance tuning, and hypercare.
- Best Practices & Governance: Champion enterprise data governance (Unity Catalog), DataOps, CI/CD pipelines, and cost-optimization strategies within client environments.
- Stakeholder Management: Deliver engaging technical presentations, workshops, and solution demos to both technical and non-technical audiences.
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Role Requirements & Qualifications
Core Requirements (Non-Negotiable)
- 4+ Years of Data Engineering Experience: Proven track record building enterprise ETL/ELT pipelines, data lakes, and data warehouses.
- 4+ Years of Consulting / Client-Facing Experience: Demonstrated success in technical consulting, solution design, client management, and delivering engagements within agency, SI, or professional services environments.
- Certifications: Must hold the Databricks Certified Data Engineer Professional credential (or actively maintained equivalent).
- Proven Databricks Track Record: Minimum of 2 to 3 enterprise-scale projects delivered with hands-on, end-to-end implementation experience on Databricks.
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Technical Skillset
- Databricks Stack: Deep experience with Delta Lake, PySpark/Spark SQL, Delta Live Tables (DLT), Unity Catalog, Databricks Workflows, and Auto Loader.
- Languages: Advanced proficiency in Python and SQL.
- Cloud Infrastructure: Strong hands-on experience on at least one major cloud provider platform (AWS, Azure, or GCP).
- Data Modeling & Architecture: Expertise in Medallion Architecture (Bronze/Silver/Gold), dimensional modeling, and real-time/batch processing.
- DevOps & Software Engineering: Experience with Git, CI/CD tools (e.g., Azure DevOps, GitHub Actions), and infrastructure-as-code principles.
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