Senior Data Engineer in London

Senior Data Engineer in London

London Full-Time 77500 £ / year Home office (partial)
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At a Glance

  • Tasks: Lead the development of robust data pipelines and optimise Azure Databricks for economic analysis.
  • Company: Join a leading financial services firm with a focus on innovation and collaboration.
  • Benefits: Competitive salary, hybrid work model, bonuses, and comprehensive benefits.
  • Other info: Opportunity for mentorship and career growth in a dynamic environment.
  • Why this job: Make a significant impact in economic data engineering while working with cutting-edge technology.
  • Qualifications: 10+ years in data engineering, expertise in Azure Databricks, and strong coding skills.
  • Senior Data Engineer – Monetary Analysis & Economic Data
  • Location: London, UK (Hybrid: 3 days in office, 2 days remote)
  • Security Clearance: SC Clearance Required (Active or eligible to undergo)
  • Salary: £75,000 to £80,000 + Benefits and Bonus
  • Position Type: Full-Time, Permanent
  • Experience Level: 10+ Years (Senior/Lead)

About the Role

We are seeking an expert Hybrid Data Engineer to work in London 3 days in office, 2 days remote paying £75,000 to £80,000 + Benefits and Bonus to drive the development, optimization, and scaling of our cutting-edge Azure Databricks platform.

This high-performance infrastructure is critical to our core mission, directly powering our Monetary Analysis, Forecasting, and Modelling frameworks.

In this role, you will lead the engineering of robust, secure data pipelines, implement complex transformation logic, and guarantee absolute data reliability for business-critical economic datasets.

Key Responsibilities

  • Data Pipeline Engineering & Processing
  • Build & Scale: Design, develop, and maintain robust, scalable ETL/ELT pipelines ingesting data from APIs, relational databases, streaming services, and financial data providers.
  • Complex Transformations: Implement advanced data processing logic for cleaning, enriching, and aggregating large-scale data using Spark (Py Spark/Scala) and SQL.
  • Optimization: Fine-tune data workloads for maximum performance, throughput, and cloud cost-efficiency.
  • Azure Databricks & Cloud Architecture
  • Platform Ownership: Drive the implementation of Azure Databricks services, leveraging Unity Catalog and Delta Lake architectures.
  • Polyglot Development: Develop and maintain data solutions using a diverse technical stack including Python, SQL, R, YAML, and Java Script.
  • Data Quality, Governance & Security
  • Data Governance: Lead hands-on implementation of Azure Purview to manage data quality, data governance, metadata, and end-to-end data lineage tracking.
  • Framework Design: Establish automated data validation, quality checks, and real-time alerting processes across all production environments.
  • Dev Ops, Automation & Collaboration
  • CI/CD Integration: Partner with Dev Ops teams to design, build, and maintain robust CI/CD pipelines for automated environmental deployments.
  • Cross-Functional Partnership: Collaborate closely with economists, data scientists, and senior analysts to translate complex analytical needs into production-ready data systems.
  • Mentorship & Quality: Drive engineering excellence through active participation in code reviews, architectural discussions, and knowledge-sharing sessions.
  • Technical Stack & Qualifications

Essential Experience

  • Core Data Engineering: 10+ years of dedicated data engineering experience managing massive, complex datasets.
  • Azure Databricks Expertise: 3+ years of deep, hands-on production experience with Azure Databricks, Spark (Py Spark/Scala), and Delta Lake ecosystems.
  • Cloud Infrastructure: Extensive experience across the Azure data suite, specifically Azure Data Factory, Azure Blob Storage, and Azure SQL Database.
  • Core Languages: Strong proficiency in Python, Spark, and SQL.
  • Technical & Architectural Familiarity
  • Governance Tools: Practical experience using Azure Purview for governance and cataloguing.
  • Languages & Infrastructure: Working knowledge or exposure to R, YAML, and Java Script within data workflows.
  • Streaming & Dev

Ops: Experience with event-driven data (e. g., Kafka, Azure Event Hubs) and modern Dev Ops tooling (Azure Dev Ops, Git, Docker, Kubernetes).

  • Data Layering: Solid understanding of both SQL and No SQL database design, data warehousing principles, and data modelling techniques.
  • Domain & Interpersonal Skills
  • Industry Background: Experience working within financial services, central banking, or an economic data environment is highly advantageous.
  • Communication: Exceptional ability to bridge the gap between technical infrastructure and economic/analytical business logic.
  • Certifications (Preferred): Microsoft Certified: Azure Data Engineer Associate or Databricks certifications

Senior Data Engineer in London employer: Velocity Talent

Join a forward-thinking company in Leeds that values innovation and collaboration, offering a hybrid work model that promotes work-life balance. With competitive salaries and a strong focus on employee growth through continuous learning and development opportunities, this is an excellent place for Senior Java AWS Developers to thrive. The supportive Agile environment encourages creativity and teamwork, making it a rewarding workplace for those looking to make a meaningful impact in the tech industry.

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Contact Details:

Velocity Talent Recruitment Team

We think you need these skills to ace Senior Data Engineer in London

SQL
Python
Problem-Solving Skills
Communication Skills
Automation
Data Engineering
Data Governance