Senior Data Engineer

You'll own the company's data lake, managing millions of financial events daily (bets, wallet movements, and live odds) across 12M+ active users. You'll define how data is ingested, stored, retained, and governed across S3 and Snowflake/Databricks, ensuring accurate, reconciled, and reliable data for analytics, finance, and regulatory needs.
Key Responsibilities
Own lakehouse architecture, including Bronze/Silver/Gold layers, Iceberg/Delta tables, and schema evolution.
Build CDC streaming pipelines using Kafka, Debezium, or similar technologies, handling late and duplicate events.
Optimize data storage and query performance through partitioning, compaction, and file sizing.
Manage data retention, archival, regulatory requirements, and GDPR deletion.
Ensure data accuracy through freshness SLAs, drift detection, and reconciliation with wallet and ledger systems.
Own data governance, including cataloging, lineage, access control, PII masking, encryption, and audit trails.
Monitor ingestion health, data quality, 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 storage (S3/GCS) and Snowflake, Databricks, or BigQuery.
Hands-on experience with open table formats (Iceberg, Delta, or Hudi).
Strong understanding of partitioning, file layout, and query optimization at terabyte 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 financial ledger systems.
Experience with data governance, including catalogs, lineage, access control, PII, and retention.
Python and workflow orchestration experience (Airflow, Dagster, or similar).
Hands-on experience building and deploying AI agents and LLM-powered workflows to automate complex processes at scale.
Nice to have: Experience in fintech, iGaming, or other regulated, audit-heavy industries.