Are you an experienced Data Engineer looking for your next big challenge?
Do you have a passion for football?
Why not bring the two together?
This is a unique opportunity to work at the cutting edge of AI, data technology, and elite football analytics. As a Data Engineer, you’ll join a collaborative, high-performing team with a culture rooted in creativity, innovation, and excellence.
In this role, you’ll design and develop scalable data pipelines and infrastructure that power decision-making across every area of the club — from strategy, tactics, recruitment, and performance, to pre- and post-match analysis. You'll also play a key role in supporting the club’s commercial operations, including e-commerce and fan engagement.
If you're passionate about using advanced data engineering to drive real-world impact in sport, this is the role for you.
Key Responsibilities
Architect, design and build scalable and high-performance data pipelines
Ensure all systems adhere to best practices for data quality, integrity, and security
Integrate modern data engineering tools and technologies into cloud-native infrastructure
Develop tools and solutions to support sports data modeling, analytics, and predictive insights
Collaborate with data scientists, analysts, and performance experts to enable end-to-end data workflows
Own the architecture and maintenance of a GCP-based data lake/lakehouse environment
Your Background
4+ years
of industry experience in
Data Engineering
roles
Advanced-level
Python
for data applications and high proficiency in
SQL
(query tuning, complex joins)
Hands-on experience designing and deploying
ETL/ELT pipelines
Proficiency in
data architecture, data modeling,
and
scalable storage design
Solid engineering practices:
Git and CI/CD
for data systems
Highly Desirable Skills
GCP Stack:
Hands-on expertise with
BigQuery, Cloud Storage, Pub/Sub,
and orchestrating workflows with
Composer
or
Vertex Pipelines.
Domain Knowledge:
Understanding of
sports-specific data types
(
event, tracking, scouting, video
)
API Development:
Experience building data-centric
APIs
using
FastAPI
, especially in
serverless environments
(e.g.,
Google App Engine)
Streaming Data:
Familiarity with
real-time data pipelines
and data ingestion at scale
DevOps/MLOps:
Exposure to
Terraform
,
Docker
,
Kubernetes
, and
MLOps workflows
What They Offer
A chance to work on
real-world data
that impacts
elite football performance
Access to
high-value datasets
, sports science teams, and cross-disciplinary experts
A
flexible hybrid working model
(1 day per week in the London office)
The opportunity to grow within a
digital-first team
at a
world-renowned football club
The satisfaction of applying your engineering skills in an environment where your work
directly influences results on the pitch