Full job description

We are seeking an experienced Lead Data Engineer with deep expertise in Python, Databricks and Spark to lead the delivery of large-scale data engineering initiatives.

This is a unique opportunity for a technical leader who enjoys combining hands-on engineering with project delivery, team leadership and stakeholder engagement in a complex enterprise environment.




Client Details


Our client is a leading international financial institution with a long-established presence across major global markets. Serving a diverse client base that includes corporates, financial institutions and investors, the organisation delivers a broad range of banking, financing and capital markets services.
With significant investment in digital transformation and data-led innovation, the organisation is modernising its technology estate and expanding its enterprise data capabilities. Data plays a critical role in supporting business operations, regulatory obligations, analytics and strategic decision-making, making this an exciting opportunity to contribute to large-scale, business-critical data initiatives within a complex global environment.




Description
*Lead the end-to-end delivery of data engineering projects, ensuring successful outcomes against business objectives, timelines and quality standards
*Design, develop and optimise scalable data pipelines using Python, Databricks and PySpark
*Build and enhance ETL/ELT workflows, reusable frameworks and modern data engineering solutions
*Provide technical leadership and architectural guidance across data platform initiatives
*Design and govern Lakehouse architectures leveraging Databricks and Delta Lake
*Manage sprint planning, backlog prioritisation and delivery tracking within Agile teams
*Identify and mitigate delivery risks, dependencies and technical challenges
*Troubleshoot complex data, platform and performance-related issues
*Drive engineering best practices across coding standards, testing, performance optimisation and code reviews
*Act as a key interface between business stakeholders and engineering teams, translating requirements into scalable technical solutions
*Collaborate with architects, product owners and senior stakeholders to shape delivery roadmaps and technical direction
*Lead, mentor and develop a team of data engineers, fostering a culture of ownership and engineering excellence
*Ensure data quality, governance, reliability and security across data platforms
*Implement monitoring, logging and alerting capabilities to support operational excellence
*Champion modern engineering practices, including CI/CD, DevOps and automation
*Support production environments and drive continuous improvement across data solutions


Profile


You will bring:
*10+ years’ experience in data or software engineering
*Proven experience as a Lead Data Engineer, Technical Lead, Engineering Lead, or similar hands-on leadership role
*Strong hands-on expertise in Python
*Extensive experience with Databricks, including workflows, notebooks and Delta Lake
*Strong experience with Apache Spark / PySpark
*Experience building and optimising enterprise-scale ETL pipelines
*Strong understanding of modern data architecture and Lakehouse concepts
*Advanced SQL and distributed data systems expertise
*Experience with cloud platforms such as AWS, Azure or GCP
*Experience working within Agile delivery environments
*Excellent stakeholder management and communication skills
*Ability to balance technical leadership with hands-on delivery responsibilities
*Experience delivering data engineering solutions within Banking, Financial Services, Capital Markets, Insurance, or other highly regulated enterprise environments would be highly advantageous
Desirable experience includes:
*Databricks certifications
*Kafka or Structured Streaming
*CI/CD and DevOps practices
*Airflow or Databricks Workflows
*Delta Lake optimisation techniques
*Docker and Kubernetes
*Exposure to machine learning pipelines




Job Offer


*Competitive day rate of £650-880 per day Inside IR35 (Umbrella)
*Initial 6-month contract
*Hybrid working arrangement - 2/3 days onsite
*Opportunity to lead strategic data transformation initiatives
*Access to modern cloud and data engineering technologies
*Significant influence over technical direction and delivery
*Collaborative, high-performing engineering environment