Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Python Data Engineer - Vanguard

Vanguard
London
3 days ago
Create job alert

We are looking for Server-Side Python/AWS engineer to join a Full-Stack team in Data Engineering embracing new ways of working (NWoW) in the Global Investments Financial Systems (GIFS) division.

We are rapidly expanding our European technology presence, so this is an exciting opportunity to join the team and help grow and influence team direction, whilst learning about the Investment Management apparatus at Vanguard.

The role will involve close work with Vanguard's funds data, allowing exposure to understanding the investment acumen, as well as work on leading technologies using Cloud Native architecture - Python, AWS services (IAM, S3, ECS, EMR, AWS Lambda, Athena, DynamoDb, etc.) and Knowledge Graphs.

The team uses agile methodologies and operates leveraging a continuous delivery pipeline - deploying daily.

About Us

Vanguard is one of the world's largest investment management companies, with around 380 low-cost traditional funds and ETFs, operating in 19 locations worldwide with about 18,800 crew members.

For us, investing doesn't just end in value. It starts with values. Because when you invest with courage, when you invest with clarity, and when you invest with care, you get so much more in return. We invest with purpose-and that's how we've become a global market leader. Here, we grow by doing the right thing for the people we serve. And so can you.

We want to make success accessible to everyone. This is our opportunity. Let's make it count.

The Role

We are looking for Server-Side Python/AWS engineer to join a Full-Stack team embracing new ways of working ( NWoW) in the Global Investments Financial Systems (GIFS) division in our offices in London.
We are rapidly expanding our European technology presence, so this is an exciting opportunity to join the team and help grow and influence team direction, whilst learning about the Investment Management apparatus at Vanguard.

The role will involve work on leading technologies using Cloud Native architecture - Python, AWS services (IAM, S3, ECS, EMR, AWS Lambda, Athena, DynamoDB, etc.) and Knowledge Graphs. The team uses agile methodologies and operates leveraging a continuous delivery pipeline.
The projects will involve applications related to Investment Product Data Engineering, Data and Workflow Management. Experience implementing Python micro-services patterns for enterprise scale is a requisite. Furthermore, a demonstrable working knowledge of AWS core services stack is requisite. Experience with manipulating avro files and understanding knowledge graphs is not mandatory, but will be seen as an advantage.

The successful candidate will be a self-starter and demonstrate an aptitude for learning and problem solving, as well as a propensity for testing and documentation.

The team will have daily interaction with the Business Product Manager and Business Users in the Products team, so excellent written and oral communication skills are imperative.

In this role, you will:

  • Be part of a business facing IT team to deliver new solutions to the business, understand/review functional specifications and translate into program specifications, liaise with end users for user acceptance testing, and provide 3rd line support as required
  • Build thought leadership and expertise around best-practice solution design and implementation
  • Comply with defined code and documentation standards, including peer reviews
  • Be a self-starter with the ability to effectively manage time across multiple projects and with competing business demands and priorities

What it takes

  • Experience in Test Driven Development and strong knowledge of Python and object oriented programming
  • Experience in software development using cloud technologies (AWS preferred)
  • Knowledge of build/deployment/testing/logging/monitoring tools and frameworks like Git/Github, and Splunk.
  • Knowledge of SQL and databases like PostgreSQL
  • Knowledge of Data Engineering in Python using libraries like Pandas, fastavro etc.
  • Understanding of investment management domain with strong analytical, problem solving and communication skills
  • Ability to work well with both business managers and operations team, and ability to perform well under pressure, and deliver to tight deadlines
  • Knowledge of agile software development process/practices and familiarly with JIRA, Confluence, and other tools
  • A good grounding of the Buy-side, and Equities knowledge is preferable, but is not a pre-requisite.

Special Factors

  • Vanguard is not offering sponsorship for this position
  • This is a hybrid position and would require you to work in the London office Tuesday-Thursday

Inclusion

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.

Our core purpose

To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

As we develop the path forward, we will take a thoughtful approach that both maximizes the advantages of working remotely and the many benefits of coming together and collaborating in a shared workspace. We believe that in-person interactions among our crew are important for preserving our unique culture and advantageous for the personal development of our crew.

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.

Related Jobs

View all jobs

Python Data Engineer - Vanguard

GenAI Data Engineer

Quantitative Developer Python C++ - MFT

Junior Data Scientist

Senior Data Scientist

Data Scientist - Reigate

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.