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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Cloud Data Engineer - KSP - **Company:** FDJ UNITED - **Location:** London, UK - **Experience:** Expert - **Salary:** £89,346.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Data Analysis, Cloud Database, Information Engineering, Data Governance, Data Transformation, Digital Assets, Digital Data, Distributed Systems, Apache Hive, Machine Learning, Metadata, Meta-Data Management, Standard Sql, SQL Databases, Data Streaming, Data Processing, Cloud Platform System, Feature Engineering, Apache Spark, Data Layers, Event Driven Architecture, Build Management, Apache Flink, Real Time Data, Apache Kafka, Data Management, Machine Learning Operations, Video Streaming, Data Pipelines - **Published:** September 11, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5878642575 ## About the Role * 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. ## Description * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london)