Smarkets is transforming the betting exchange space by delivering world-class technology and the best-priced markets in the industry. With over £35 billion in traded volume since 2010, we’ve built a product-led, transparent, and fair platform that challenges the norms of traditional betting.
As a Series B tech company, we pride ourselves on engineering excellence, lean product thinking, and scientific rigor. With a close-knit team and a passion for innovation, Smarkets is where top talent comes to make a real impact.
Now, we’re looking for a Data Engineer to help take the wealth of Data that we generate and use it to drive insights to improve the business.
You’ll join the Data Team, the group that transforms Smarkets’ vast streams of data into insights and systems that power decisions across the business. From sports event data and payments, to order flow and user analytics, you’ll work with some of the most diverse and high-volume data in the industry.
This isn’t just data engineering—you’ll be building the pipelines, services, and platforms that underpin our analytics, ML models, and business reporting. You’ll shape how we collect, process, and serve data at scale, creating the foundations for smarter decisions and better products.
Design and Own Pipelines: Build and maintain ETL pipelines (batch and real-time) that turn raw data into reliable, usable insights.
Build Data Services: Develop Python/Flask APIs and Postgres services that expose data and manage business entities.
Support Analytics & Reporting: Automate reporting pipelines, design data models, and empower teams with accurate dashboards.
Enable Data Science: Train and deploy ML models for segmentation, anomaly detection, and recommendations—contributing to our existing recommender service.
Operate Data Infrastructure: Keep our data warehouses (Redshift, BigQuery) healthy, scalable, and performant.
Collaborate & Mentor: Work closely with data scientists, analysts, and engineers across teams, helping raise the bar for data excellence.
Your Toolkit
Languages & Frameworks: Python (pandas, NumPy, scikit-learn), Flask, Bash.
Pipelines & Orchestration: ETL frameworks such as Luigi or Airflow.
Data Infrastructure: PostgreSQL, AWS Redshift, Google BigQuery, dbt, Kafka.
Ops & Monitoring: Docker, Kubernetes, Jenkins, Prometheus, Grafana, ElasticSearch, Kibana, Sisense.
ML & Analytics: Model training and deployment workflows, user segmentation, anomaly detection.
Professional experience in data engineering.
Hands-on experience building ETL pipelines in Python.
Background in developing APIs/services with Python and databases.
Familiarity with the Python data science stack and deploying ML models.
An eye for writing maintainable, well-tested code.
A collaborative, proactive attitude and a desire to learn.
A degree in Computer Science, Math, or equivalent experience.
Push to win
Make others better
Give a shit
Be a pro
Bring the energy
Our values shape everything we do—from how we build systems to how we support each other. We want engineers who care about impact, quality, and team success.
Stock options with 4-year vesting
6% matched pension scheme via Aviva
Health insurance
Daily in-office lunch prepared by our chef, plus snacks, coffee, and drinks
Cycle to work scheme
£1,000 yearly education budget for courses, books, or conferences
25 days paid holiday + bank holidays, with 5 carry-over days
Flexible hybrid model (2 days a week from home)
20 days per year of global working