Data Engineering Technical Lead
AI in this role
Job Title
Data Engineering Technical Lead
The Role
The Data Engineering Technical Lead will play a critical role in shaping and delivering Vanguard Europe's data and analytics capabilities. Working within the Chief Data & Analytics Office (CDAO), this role will lead the technical design, development, and evolution of data products that support business decision-making across Financial Advice Services, Marketing, Operations, Risk, and other key business functions.
Lead the design, development, and optimization of scalable data platforms and data products on AWS tech stack and Databricks. Drive engineering best practices, mentor data engineers, and deliver high-quality data solutions that support analytics, reporting, and AI initiatives.
In this role you will
· Design and build scalable data pipelines using Databricks, PySpark, SQL, AWS Glue and Lambda.
· Develop and manage Data Lake solutions using Bronze, Silver, and Gold data architectures.
· Implement batch and real-time data processing using Spark Structured Streaming and Auto Loader.
· Optimize Databricks workloads for performance, scalability, reliability, and cost efficiency.
· Establish data quality, governance, and security controls using Unity Catalog and enterprise best practices.
· Lead technical delivery, code reviews, and engineering standards across the data engineering team.
· Collaborate with Product Managers, Architects, Analysts, and business stakeholders to deliver data products.
· Implement CI/CD and Infrastructure as Code using Terraform and modern DevOps practices.
· Mentor engineers and promote best practices in Databricks and data engineering.
What it takes
Must-Have Skills & Experience
· Expert-level experience with Databricks, PySpark, SQL, and Apache Spark
· Strong experience designing and delivering cloud-based data platforms and lakehouse architectures
· Hands-on experience with Delta Lake, Unity Catalog, Databricks Workflows, and performance tuning
· Experience building batch and streaming data pipelines
· Strong knowledge of data modelling and data product design
· Experience with Terraform, Git, CI/CD, and automated testing
· Proven leadership and stakeholder management skills
.
Nice-to-Have Skills & Experience
· AWS data platform experience
· Experience with Delta Live Tables (DLT) and MLflow
· Knowledge of AI/ML, MLOps, and Generative AI solutions on Databricks
· Financial Services industry experience
Special Factors
· Vanguard is not offering visa sponsorship for this position
· This is a hybrid position and would require you to work in the office 3 days per week (Tuesday, Wednesday & Thursday)
· Please note that we review applications on a rolling basis and may close this role early if there is a high level of interest. To avoid missing out, we recommend applying as soon as possible
Why Vanguard?
Vanguard is a different kind of investment company. It was founded in the United States in 1975 on a simple but revolutionary idea: that an investment company should manage its funds solely in the interests of its clients.
This is a philosophy that has helped millions of people around the world to achieve their goals with low-cost, uncomplicated investments.
It's what we stand for: value to investors.
Inclusion Statement
Vanguard’s continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: “Do the right thing.”
We believe 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. We empower our crew to contribute their distinct strengths to achieving Vanguard’s core purpose through our values.
When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we 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.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
How we rate this
Data Engineering Technical Lead at Vanguard rates 24 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used Mlflow in your day-to-day work.
- What are the limits of Databricks that you've run into, and how did you work around them?
Adapt your resume
- List these exact terms on your resume: ML Ops, Mlflow, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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