The Role You'll own the data lake — the system of record for millions of financial events a day across million of active users. You decide how that data lands, is stored, retained, and governed on S3 + Snowflake/Databricks, so analytics, finance, and regulators all see accurate, reconciled data with zero drift from source.
What you'll be doing 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.




What we're looking for 3+ years in data engineering, with real ownership of a large-scale data lake or lakehouse.
Cloud object storage (S3/GCS) plus Snowflake, Databricks, or BigQuery in production.
Hands-on with an open table format (Iceberg, Delta, or Hudi).
Deep understanding of partitioning, file layout, and query optimization at terabyte-plus scale.
CDC and streaming ingestion experience (Kafka + Debezium or equivalent).
Strong SQL and data modeling; enough relational grounding to reason about the OLTP systems you capture from — critical for financial ledgers.
Data lake governance: catalogs, lineage, access control, PII, retention.
Python and an orchestrator (Airflow/Dagster) as tools — this is an architecture and ownership role, not heads-down coding.
Nice to have: fintech, iGaming, or another regulated, audit-heavy environment.

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📌 Data Engineer (Veracruz)
🏢 Pentasia
📍 Veracruz