Senior Data Engineer

Tip: Full time
Nivel: Senior
Experiență: Mai mult de 5 ani

Departament: IT
Locație: București

We are rebuilding the foundations of our data platform: moving from a fragmented setup toward a cloud-centered lakehouse, standardizing transformations with dbt, orchestrating with Airflow and preparing for a major possible change of event flows and identity modeling. You will be the senior hands-on engineer who turns this into a reliable, documented, testable data foundation that powers our tools and analytical/predictive systems.

What you should do:

Implement a clear layered model (00 raw/landing, staging, intermediate, marts/30).
Co-build with AI Infra engineer, scalable BigQuery datasets: partitioning/clustering strategies, cost/performance optimization.
Define canonical business tables for our business needs.
Implement dbt project structure, naming conventions, documentation, tests.
Build incremental models, snapshot patterns (SCD), and clear semantic definitions.
Enforce quality gates: schema tests, uniqueness, freshness, anomaly checks.
Productionize DAGs for ingestion + dbt runs + monitoring.
Add observability: SLAs, retries, alerting, backfills, lineage.
Ensure reliable refresh cadence for our tools and ML flows.
Build/own ingestion patterns from source systems into BigQuery
Prepare for the new platform migration: adapt pipelines to new event schemas and identity model; maintain continuity for analytics and ML.

What we want you to know:

Senior-level SQL + data modeling (dimensional + analytics engineering patterns).
Strong Cloud Data Lake expertise (BigQuery, Databricks, Snowflake, etc.)
dbt in production: tests, docs, incremental models, CI checks.
Airflow: DAG design, retries, backfills, alerts.
Strong Python for pipeline utilities, data validation, and integration glue.
Production mindset: monitoring, incident handling, reproducibility, documentation.

Nice to have: