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Data Engineering Team Lead - Databricks

Job Description - Data Engineering Team Lead - Databricks

Description

We are working with a leading global Financial Services business to hire an experienced Data Engineering Team Lead to head up a team of engineers working across a large-scale enterprise data platform. This is a senior hands-on leadership role requiring both deep technical expertise and the ability to drive delivery, mentor talent, and set standards across a distributed engineering function.

Responsibilities:

  • Lead, mentor, and develop a team of data engineers across multiple locations, driving code reviews, design reviews, and a culture of knowledge-sharing
  • Own and drive Agile/Scrum delivery processes, ensuring the team operates effectively against roadmap priorities
  • Design and develop scalable data solutions on a Lakehouse architecture platform, supporting enterprise-wide data processing and analytics
  • Build, optimise, and maintain ETL/ELT pipelines and structured streaming workflows for both batch and real-time data ingestion
  • Configure and tune clusters and Spark jobs to deliver consistent performance at scale
  • Utilise Delta Live Tables and Unity Catalog to manage data ingestion, transformation, and access governance
  • Apply IAM best practices and uphold compliance with data security and governance standards
  • Support infrastructure provisioning and resource management using Terraform
  • Implement monitoring frameworks covering pipeline performance, data quality, and operational health
  • Contribute to technical documentation and promote continuous improvement across the engineering practice


Requirements
  • 8+ years in data engineering, with at least 3 years hands-on experience with Databricks
  • Proven experience leading and managing a team of data engineers
  • Strong Python and Spark programming skills
  • Solid AWS experience across core services including S3, Glue, and Lambda
  • Deep understanding of data modelling, SQL, and ETL/ELT design patterns
  • Experience with Delta Lake, Lakehouse architecture, and Git-based version control
  • Demonstrable use of AI tools within a professional development workflow
  • Strong leadership, communication, and stakeholder management skills

Desirable:

  • Financial services or fund administration background
  • Exposure to AI/ML implementation patterns and real-time data processing frameworks
  • Multi-cloud experience beyond AWS
  • API development or data governance framework experience
  • Track record of developing junior and mid-level engineers in a fast-paced environment


Benefits

Salary: to be discussed, depending on experience

Length: Permanent contract

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