We’re looking for a Mid Data Engineer to take ownership of our data lake — the system of record for millions of financial events every day, including bets, wallet transactions, and live odds, serving 12M+ active users. You’ll be responsible for designing and maintaining reliable data pipelines and defining how data is ingested, stored, retained, reconciled, and governed across AWS S3 and Snowflake/Databricks. Your work will ensure that Analytics, Finance, and Regulatory teams have access to accurate, consistent, and fully traceable data — with zero drift from source systems.
Location: Kraków, Poland. Hybrid — 2 days per week from the office.
What you will do:
- Own the lakehouse architecture: bronze/silver/gold layers, Iceberg/Delta tables, schema evolution.
- Land operational data via CDC streaming (Kafka, Debezium), handling late and duplicate events.
- Design data layout for speed and cost: partitioning, compaction, file sizing, query performance on Trino/Athena/Snowflake.
- Own retention and archival: storage tiering, regulatory retention, immutability, GDPR deletion.
- Guarantee correctness: freshness SLAs, drift detection, reconciliation against the source wallet and ledger systems.
- Own governance: catalog and lineage, row/column access control, PII masking, encryption, audit trails.
- Monitor ingestion health, data anomalies, and cloud storage/compute spend.
Must-have:
- 2 years of hands-on in a production lakehouse environment.
- Lakehouse architecture — bronze/silver/gold layering, an open table format (Iceberg, Delta, or Hudi), schema evolution.
- Data layout & query optimization at TB+ scale — partitioning, compaction, file sizing, query performance on Trino/Athena/Snowflake.
- Cloud lakehouse/DWH in production — Snowflake, Databricks, or BigQuery.
- CDC & streaming ingestion — Kafka + Debezium or equivalent; late, duplicate, and out-of-order events.
- Strong SQL and data modeling — enough relational grounding to reason about the OLTP systems you capture from. Critical for financial ledgers.
- Correctness — freshness SLAs, drift detection, reconciliation against source wallet/ledger systems.
- Governance — catalogs, lineage, row/column access control, PII masking, retention, GDPR deletion.
- Cloud object storage — S3 or GCS, plus storage tiering and archival.
- Python and an orchestrator — Airflow or Dagster, as tools.
Skills Required
- At least 2 years of hands-on experience in a production lakehouse environment
- Experience with lakehouse architecture, including bronze, silver, and gold layers, open table formats, and schema evolution
- Experience with data layout and query optimization at TB-plus scale, including partitioning, compaction, file sizing, and query performance
- Production experience with Snowflake, Databricks, or BigQuery
- Experience with CDC and streaming ingestion using Kafka, Debezium, or equivalent
- Strong SQL and data modeling skills with relational OLTP systems knowledge
- Experience implementing freshness SLAs, drift detection, and reconciliation against source systems
- Experience with data governance, catalogs, lineage, row and column access control, PII masking, retention, and GDPR deletion
- Experience with cloud object storage such as S3 or GCS, including storage tiering and archival
- Python and experience with an orchestrator such as Airflow or Dagster
What We Do
Commit is a global tech services company with offices in Israel, US, Canada, UK, and Europe. The company was founded in 2005 and has over 700 multi-disciplinary innovation experts who serve a broad range of companies, from small startups to large enterprises in multiple business sectors. Commit specializes in advanced technologies and applications with dedicated practices in Cloud, GenAI, Software, IoT, Big Data, Cyber, Collaboration, Data center migration projects, and more. Commit offers innovative, end-to-end technology solutions by developing custom software and IoT platforms for clients looking to build their next-gen products within the modern ICT world. Commit’s complete and comprehensive engineering powerhouse of resources, and proprietary Flexible R&D methodology helps transform its clients’ technology visions into high-quality products while reducing costs and improving time-to-market.
