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

Apply Now

Senior Data Engineer

Williams Racing
Wantage
3 days ago
Create job alert
Overview

We are looking for a Senior Data Engineer to join our Technology & Innovation Group. As a Senior Data Engineer, you will play a key role in shaping the future of Atlassian Williams Racing’s data platform. You will be responsible for designing, implementing, and evolving scalable, secure, and high-performance data infrastructure and pipelines, while also contributing to the strategic direction of our data architecture.

This role bridges deep technical expertise with business context, ensuring the data engineering layer effectively supports performance, operations, and innovation across the organisation. As we scale up our data platform, you will also mentor junior engineers, influence architectural decisions, and help integrate new technologies that support Williams' broader transformation journey.

Responsibilities
  • Lead the design, development, and optimisation of modern, cloud-native data pipelines and infrastructure to support large-scale, high-value data workloads across the organisation.
  • Work closely with Data Architects and the Head of Data & AI to support the development and implementation of our Data Strategy and the build-out of our data platform.
  • Evaluate and implement best-in-class technologies, frameworks, and tools for ingestion, processing, governance, observability, and storage of structured and unstructured data.
  • Collaborate across business and technical teams to identify requirements, develop solutions, and ensure that data products support analytics, AI/ML, and operational reporting use cases.
  • Champion data quality, observability, lineage, and metadata management to ensure data is trusted, discoverable, and reliable.
  • Drive cloud migration efforts, including deployment of scalable services in AWS (or other cloud environments), infrastructure as code, and automation of data operations.
  • Provide guidance and mentorship to other engineers, helping grow a culture of high-performance engineering and continuous improvement.
  • Create and maintain robust documentation of pipelines, architecture, and best practices to ensure sustainability and knowledge sharing.
Skills and experience required
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Previous, proven, hands-on experience in data engineering or software engineering with strong exposure to modern data platforms.
  • Proven expertise in building and maintaining data pipelines and ETL/ELT workflows using tools like Apache Airflow, dbt, or custom frameworks.
  • Strong experience with cloud data platforms (e.g., AWS, Azure, GCP) and distributed data systems (Spark, Kafka, or Flink, etc).
  • Proficiency in Python (or similar languages) with solid software engineering fundamentals (testing, modularity, version control).
  • Hands-on experience with SQL and NoSQL data stores, such as PostgreSQL, Redshift, DynamoDB, or MongoDB.
  • Good understanding of data warehousing and modern architectures (e.g., data lakehouse, data mesh).
  • Familiarity with DevOps/CI-CD practices, infrastructure-as-code (Terraform, CloudFormation), and containerisation (Docker/Kubernetes).
  • Understanding of data quality, observability, lineage, and metadata management practices.
Desirable
  • Experience with event-driven architectures and real-time data processing.
  • Prior exposure to data governance, cataloguing, and security frameworks (e.g., IAM, encryption, GDPR).
  • Experience in a fast-paced environment such as automotive, motorsport, or high-performance computing.
  • A track record of mentoring junior engineers and contributing to engineering culture and team standards.
Company Description

For almost 50 years, Williams Racing has been at the forefront of one of the fastest sports on the planet, being one of the top three most successful teams in history competing in the FIA Formula 1 World Championship. With an almost unrivalled heritage of engineering and racing F1 cars and unforgettable eras that demonstrate it is a force to be reckoned with, the British squad boasts 16 F1 World Championship titles to its name.

Since its foundation in 1977 by the eminent, late Sir Frank Williams and engineering pioneer Sir Patrick Head, the team has won nine Constructors’ Championships, in association with Cosworth, Honda and Renault. Its roll call of drivers is legendary, with its seven Drivers’ Championship trophies being lifted by true icons of the sport: Alan Jones, Keke Rosberg, Nelson Piquet, Nigel Mansell, Alain Prost, Damon Hill and Jacques Villeneuve. The team has made history before and is out to make it again with a long-term mission to evolve and return to the front of the grid.

Equal Opportunity

At Atlassian Williams Racing is an equal opportunity employer that values diversity and inclusion. We are happy to discuss reasonable job adjustments.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer | Cambridge | Greenfield Project

Senior Data Engineer - Azure, BI & Data Strategy

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.

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.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.