Focusing on our Sportsbook product, we’re looking for a Senior Data Engineer to help build and evolve our next-generation data platform, powering trusted, scalable, and real-time data assets across multiple brands and markets.
You’ll primarily work on our Sportsbook Data Platform — a modern, event-driven lakehouse built on AWS and aligned to medallion architecture principles — delivering high-quality, well-governed data products that support analytics, trading insight, and machine learning use cases. This platform underpins critical decision-making across trading, risk, personalisation, and analytics, and represents a key step forward in standardising and scaling our data ecosystem.
What You’ll Do
- Design and build scalable batch and streaming data pipelines, supporting ingestion, transformation, and serving layers.
- Develop and maintain data assets aligned to medallion architecture (bronze, silver, gold), ensuring clear ownership, quality, and usability.
- Model sportsbook domain data (bets, offers, rewards, digital data) into reusable, well-defined datasets for downstream consumption.
- Implement data transformation logic using modern tooling (e.g. dbt, Spark, SQL-based frameworks), ensuring consistency and testability.
- Build and optimise streaming data pipelines (Kafka/Flink or equivalent) to enable near real-time data availability.
- Ensure data quality and reliability through validation frameworks, observability, and robust handling of late-arriving or inconsistent data.
- Design data contracts and schemas that enable reliable integration between upstream event producers and downstream consumers.
- Optimise pipelines and storage for performance and cost efficiency within AWS.
- Collaborate with analytics, data science, and machine learning teams to translate business requirements into high-quality data assets.
- Contribute to data governance practices, including metadata management, lineage, and discoverability.
What You’ll Work On
- A modern sportsbook data platform built on AWS, supporting both real-time and batch data processing.
- Medallion-aligned data layers enabling progressive refinement from raw ingestion through to curated, business-ready datasets.
- Streaming pipelines that ingest and process high-volume sportsbook events (bets, pricing, settlements).
- Curated data assets powering trading analytics, risk monitoring, and customer personalisation models.
- Integration with semantic layers, BI tools, and machine learning platforms.
- Data governance and metadata tooling to improve transparency, trust, and reuse across the organisation.
Your Experience
- 5+ years experience in data engineering, building and maintaining scalable data platforms.
- Strong SQL and data modelling skills, with experience designing analytical datasets.
- Experience with modern data stack tools (e.g. dbt, Spark, Airflow, or similar orchestration and transformation frameworks).
- Experience with cloud-based data platforms, ideally AWS.
- Understanding of medallion architecture or similar data layering approaches.
- Experience working with streaming technologies (Kafka, Flink, or similar).
- Strong understanding of data quality, testing, and observability practices.
- Experience designing schemas and handling data consistency challenges in distributed systems.
- Ability to work closely with stakeholders to translate business needs into scalable data solutions.
- Proactive mindset with the ability to operate in evolving environments and iterate on solutions.
Nice to Have
- Experience in sports betting, trading, or financial data domains.
- Familiarity with event-driven architectures and real-time data products.
- Experience with semantic layers (e.g. Cube.js) or metrics-layer design.
- Exposure to data governance and metadata tools (e.g. OpenMetadata, Hive Metastore).
- Experience supporting machine learning workflows and feature engineering pipelines.
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