{"id":2297230,"url":"https://alion.io/job/fdjunited-senior-data-engineer","title":"Senior Data Engineer","company":{"id":1795857,"name":"Fdjunited","domain":"fdjunited.com","url":"https://alion.io/company/fdjunited","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Radancy","truth_index":{"grade":"B","score":75,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":86000,"max_usd":168000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":34},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"CI/CD","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Claude Code","optional":true},{"name":"Copilot","optional":true},{"name":"Cursor","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-28T00:00:00Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-12T03:46:26Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"At FDJ UNITED, we don't just follow the game, we reinvent it.\nFDJ UNITED is one of Europe’s leading betting and gaming operators, with a vast portfolio of iconic brands and a reputation for technological excellence. With more than 5,000 employees and a presence in around fifteen regulated markets, the Group offers a diversified, responsible range of games, both under exclusive rights and open to competition. We set new standards, proving that entertainment and safety can go hand in hand. Here, you’ll work alongside a team of passionate individuals dedicated to delivering the best and safest entertaining experiences for our customers every day.\nWe’re looking for bold people who are eager to succeed and ready to level-up the game. If you thrive on innovation, embrace challenges, and want to make a real impact at all levels, FDJ UNITED is your playing field.\nJoin us in shaping the future of gaming. Are you ready to LEVEL-UP THE GAME?\nSenior Data Engineer - A hands-on engineering role building and optimising scalable ETL/ELT pipelines and Lakehouse architectures across a modern multi-cloud platform using Python, Spark, Airflow, and dbt.Requires 5+ years of data engineering experience with strong expertise in SQL, CI/CD, data quality frameworks, and cloud technologies (S3, Athena, Redshift), with a plus for streaming and AI tooling experience.\nOverview\nA Senior Data Engineer position within an agile team, focused on building scalable data pipelines and modernizing a multi-cloud data platform. The role involves working with streaming technologies, Lakehouse architectures, and leveraging automation/AI to improve efficiency.\nKey Responsibilities\n Pipeline Development: Build ETL/ELT pipelines (Python, SQL), optimize Spark/PySpark jobs, manage Airflow DAGs, and implement dbt transformations.\n Lakehouse Architecture: Design medallion-style architectures using S3 and modern table formats (Iceberg, Delta Lake) with optimized layouts.\nPlatform Infrastructure: Create reusable frameworks, enforce data contracts, build CI/CD pipelines, and establish observability practices.\nData Quality: Implement validation frameworks, data contracts, and SLIs/SLOs for critical pipelines.\nRequired Experience\n 5+ years in data engineering\nStrong Python, advanced SQL, Airflow, Spark/PySpark, dbt, and CI/CD proficiency\nExperience with Lakehouse architectures, dimensional modeling, and cloud data warehouses (S3, Athena, Redshift)\nData quality frameworks, monitoring, and schema evolution expertise\nNice-to-Haves\nStreaming platforms (Kafka, Kinesis)\nAI coding assistants (Cursor, Claude Code, Copilot)\nTerraform, Kubernetes/Docker\nData catalog/metadata management experience\nWe believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. 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