Data Engineering Technical Lead

Overview

In this role you lead the design, development, and evolution of data products within Vanguard Europe to enable data-driven decision making. You will guide a data engineering team in a cloud-based environment, collaborating with product managers, analysts, and stakeholders to deliver scalable, secure data solutions. The position combines hands-on technical leadership with people leadership to raise engineering standards and promote AI-enabled software development. You’ll help shape Vanguard’s data strategy and engineering culture across a global team.

Responsibilities

• Design and implement scalable data pipelines and data products in the cloud.
• Lead all phases of solution development and ensure code quality, documentation, and reusability.
• Collaborate with internal clients and cross-functional teams to translate business needs into technical solutions.
• Develop and mentor junior data engineers, enforce data engineering standards, and contribute to enterprise data expert groups.
• Assess data quality, test thoroughly, and drive production readiness through regression testing and issue resolution with vendors.
• Define and communicate technical considerations to clients and less experienced colleagues.
• Support data governance, security, and operational controls within enterprise platforms.
• Promote AI-assisted development workflows and review software releases in CI/CD pipelines.

Key requirements

• Deep expertise in building scalable data pipelines and data products in cloud environments.
• Hands-on experience with Databricks, Spark, SQL, and Python.
• Experience with batch and real-time data processing solutions.
• Understanding of data architecture patterns (Kimball, Data Vault, dimensional modelling) and data product design principles.
• Infrastructure as Code experience (Terraform or CloudFormation).
• Experience leading technical delivery teams and mentoring engineers.
• Strong stakeholder management and ability to translate requirements into scalable solutions.
• Knowledge of data governance, data quality, security, and operational controls.
• Experience with Agile product delivery and cross-functional collaboration.
• Proficiency with AI-assisted development tools (e.g., Claude Code, Codex, GitHub Copilot).
• Nice-to-have: experience in Financial Services data solutions, AWS-native data services, and MLOps concepts.

• stakeholder management
• leadership and mentoring
• communication of complex ideas
• Databricks
• Spark
• SQL

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