Senior Data Engineer

You'll own our data lake - the system of record for millions of financial events every day, including bets, wallet movements, and live odds, across 12M+ active users. You'll be responsible for how data is ingested, stored, retained, and governed across our data infrastructure, built on S3 and Snowflake/Databricks. Your work will ensure that analytics, finance, and regulatory teams have access to accurate, reliable, and fully reconciled data. What You'll Do: Lakehouse Architecture: Own the lakehouse architecture, including bronze/silver/gold layers, Iceberg/Delta tables, and schema evolution. Data Ingestion: Land operational data via CDC streaming (Kafka, Debezium), handling late and duplicate events. Performance & Cost Optimization: Design data layouts for speed and cost efficiency, including partitioning, compaction, file sizing, and query performance on Trino/Athena/Snowflake. Data Retention & Archival: Own storage tiering, regulatory retention, immutability, and GDPR deletion. Data Quality & Reliability: Ensure data correctness through freshness SLAs, drift detection, and reconciliation against source wallet and ledger systems. Data Governance: Own catalog and lineage, row/column access control, PII masking, encryption, and audit trails. Monitoring: Monitor ingestion health, data anomalies, and cloud storage/compute costs. Requirements: 5+ years of experience in Data Engineering, with proven ownership of large-scale data lake or lakehouse architectures. Production experience with cloud object storage (S3/GCS) and Snowflake, Databricks, or BigQuery. Hands-on experience with an open table format (Iceberg, Delta, or Hudi). Deep understanding of partitioning, file layout, and query optimization at terabyte-plus scale. Experience with CDC and streaming ingestion (Kafka + Debezium or equivalent). Strong SQL and data modeling skills, with a solid understanding of relational databases and OLTP systems, particularly in the context of financial ledgers. Experience with data lake governance, including catalogs, lineage, access control, PII, and retention. Python and an orchestration tool (Airflow/Dagster) as working tools. This is an architecture and ownership role, not a heads-down coding position. Proven hands-on experience designing, building, and deploying AI agents and LLM-powered workflows in production. This goes beyond using existing AI tools or APIs and requires actual development and implementation experience. Nice to have: Experience in fintech, iGaming, or another regulated, audit-heavy environment.