Formula 1 Data Engineer Placement — 12 Months

Atlassian Williams F1 Team; Wantage; On-site; GBP 19,000 - 22,000; Full time

Benefits offered by this job

Gym access

Job summary

At Atlassian Williams F1 Team, the Industrial Placement offers 12 months of hands-on work within Formula 1, contributing to data platforms and engineering initiatives. You’ll develop practical data engineering skills, work with cloud platforms, and support day-to-day decisions in a high-performance environment.

You join the Data Engineering and Software Engineering teams to build pipelines behind wider data platforms, gaining real responsibilities from day one and applying university learning to

Qualifications

• Enrolled on an undergraduate degree in CS, data eng, software eng or maths.
• Foundational knowledge of programming (Python, Java or SQL).
• Basic understanding of databases, data structures and data handling.
• Strong analytical and problem-solving skills with a willingness to learn.

Responsibilities

• Build and test data pipeline components and ETL processes under guidance.
• Write and maintain Python and SQL scripts for data ingestion, transformation and validation.
• Investigate straightforward data quality issues and document pipelines clearly.
• Take part in code reviews and testing to promote good software engineering practice.
• Work with the team to understand how data supports race weekend decisions.

Skills

Python

Java

SQL

Data Engineering

Data Handling

Education

Undergraduate degree in Computer Science / Data Engineering / Software Engineering / Mathematics or related

Tools

ETL pipelines tools

Python scripting

Job description

At Atlassian Williams F1 Team, the Industrial Placement offers 12 months of hands-on work within Formula 1, contributing to data platforms and engineering initiatives. You’ll develop practical data engineering skills, work with cloud platforms, and support day-to-day decisions in a high-performance environment.

You join the Data Engineering and Software Engineering teams to build pipelines behind wider data platforms, gaining real responsibilities from day one and applying university learning to