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About the Role

The Data Engineering Technical Lead will shape and deliver Vanguard Europe's data and analytics capabilities. This role leads the technical design, development, and evolution of data products within a modern cloud environment (Databricks, AWS, IaC), partnering with various teams to ensure scalable, secure, and high-quality data solutions that drive business outcomes. It's an opportunity to influence data strategy, establish engineering best practices, promote AI-enabled development, and build a high-performing engineering culture.

Responsibilities

Write ETL processes, design database systems, and develop tools for real-time and offline analytic processing.
Troubleshoot software and processes for data consistency and integrity.
Integrate complex and large-scale data from various sources for business partners to generate insights and make decisions.
Translate business specifications into design specifications and code.
Write complex programs, ad hoc queries, and reports, ensuring code is well-structured, documented, and maintainable.
Partner with internal clients to understand business functions and informational needs.
Collaborate with technical and data analytics experts to implement data solutions.
Lead all phases of solution development and explain technical considerations in meetings.
Assess data quality and test code thoroughly.
Provide data analysis guidance and serve as a technical consultant.
Educate and develop junior data engineers, applying quality control to their work.
Develop data engineering standards and contribute expertise to other data expert teams.
Test and implement new software releases through regression testing.
Identify issues and engage with vendors to resolve and elevate software into production.

Requirements

Experience in data analytics, programming, database administration, or data management.
Proficient in spec-driven development using AI coding tools such as Claude Code or Codex.
Deep expertise designing and building scalable data pipelines and data products in cloud environments.
Strong hands-on experience with Databricks, Spark, SQL, and Python.
Experience developing and optimizing batch and real-time data processing solutions.
Strong understanding of modern data architecture patterns, including Kimball, Data Vault, dimensional modelling, and data product design principles.
Experience implementing Infrastructure as Code using tools such as Terraform or CloudFormation.
Experience leading technical delivery teams and mentoring data engineers.
Strong stakeholder management skills with the ability to translate business requirements into scalable technical solutions.
Experience implementing data governance, data quality, security, and operational controls within enterprise platforms.
Strong understanding of software engineering best practices including version control, CI/CD, automated testing, and code review processes.
Experience working in Agile product delivery environments and collaborating across cross-functional teams.
Demonstrated ability to drive technical decision-making and influence architecture direction.
Proficiency using AI-assisted development tools such as Claude Code, Codex, GitHub Copilot, or equivalent tools to improve engineering productivity and quality.
Experience delivering Financial Services, Wealth Management, Asset Management, or Investment platform data solutions.
Experience working with AWS-native data services and event-driven architectures.
Experience building data products that support analytics, reporting, machine learning, or AI use cases.
Knowledge of MLOps, AI Engineering, Agentic AI, or Generative AI implementation patterns.
Experience leading distributed engineering teams.
Experience establishing engineering standards, reusable frameworks, and community-of-practice initiatives.
Knowledge of data mesh, domain-driven design, and product-centric operating models.

Skills

Databricks
Spark
SQL
Python
Infrastructure as Code (Terraform, CloudFormation)
Data Governance
Data Quality
Security
Operational Controls
Version Control
CI/CD
Automated Testing
Code Review
Agile Methodologies
AI Coding Tools (Claude Code, Codex, GitHub Copilot)
AWS
Event-Driven Architectures
MLOps
AI Engineering
Agentic AI
Generative AI
Data Mesh
Domain-Driven Design

Location

Hybrid

Work Type

Hybrid
Full-time

Experience Level

Lead
Senior

About the Company

Vanguard is a different kind of investment company, founded in 1975 with the principle of managing funds solely in the interests of clients.
This philosophy has helped millions achieve their goals with low-cost, uncomplicated investments.
Vanguard's continued commitment to diversity and inclusion is rooted in its culture, guided by the principle of 'Do the right thing'.
They believe building diverse, inclusive, and effective teams amplifies collaboration and innovation.
Vanguard has implemented a hybrid working model to balance flexibility with in-person learning, collaboration, and connection.

Equal Opportunity

Vanguard believes that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve.
They empower their crew to contribute their distinct strengths to achieving Vanguard’s core purpose through their values.
When all crew members feel valued and included, their ability to collaborate and innovate is amplified, and they are united in delivering on Vanguard's core purpose: to take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.