Teams at FDJ UNITED

Build and optimize scalable ETL/ELT pipelines, Spark jobs, Airflow DAGs, and dbt transformations. Design Lakehouse architectures using S3, Iceberg, and Delta Lake; develop reusable platform frameworks, CI/CD pipelines, data contracts, observability, and data quality controls. The role also supports streaming technologies, cloud data warehouses, dimensional modeling, schema evolution, and AI-enabled engineering improvements.

Build and maintain batch and streaming data pipelines for a modern AWS sportsbook data platform. Develop medallion-aligned datasets using SQL, dbt, Spark, and related tools; support Kafka or Flink streaming; implement data quality checks, schemas, monitoring, and governance; and troubleshoot pipeline performance and costs. Collaborate with analytics, data science, machine learning, trading, risk, and personalization teams to deliver reliable, scalable data assets.

Designs and implements data quality frameworks across batch and streaming pipelines on an AWS data platform. Responsibilities include validation checks, observability, anomaly detection, alerting, data contracts, schema validation, root cause analysis, quality SLAs, metadata management, lineage, and governance. Partners with data engineers, analysts, and business stakeholders to improve the reliability, discoverability, and trustworthiness of sportsbook data supporting analytics, trading, and machine learning.