About The Role

Join Hack The Box as a Senior Data Engineer, where you'll own and evolve our data pipelines on GCP. You'll work end-to-end on streaming and batch pipelines, design ELT/ETL processes, and partner with ML engineers. This role offers a chance to drive the migration off Snowflake onto our GCP-native stack and continuously improve data quality, reliability, and cost efficiency. Enjoy benefits like 25 annual leave days, private insurance, and a dedicated budget for training and professional development.

Posséder et faire évoluer les pipelines de données sur GCP, en construisant de nouveaux pipelines, en renforçant les existants et en améliorant la qualité des données.
Travailler de bout en bout sur les pipelines de streaming et de batch, de l'ingestion d'événements à la transformation, au service et à la couche de fonctionnalités qui alimente nos produits ML et AI.
Collaborer avec les ingénieurs ML sur les pipelines de fonctionnalités, surveiller la dérive des données et maintenir les modèles bien alimentés et réentraînés.
Solid SQL and strong Python — you write production-quality code, not just notebooks
Working knowledge of ML in production — feature engineering, feature stores, model deployment, drift monitoring, retraining
Workflow orchestration experience with Airflow (or Prefect/Dagster)
Experience with ClickHouse or another columnar OLAP engine in production
CI/CD mindset, infrastructure-as-code sensibility, and a bias for simple, observable systems
Bonus: CDC tooling (Datastream, Debezium), Vertex AI / Feature Store
Docker & Kubernetes experience
Strong data modelling and warehouse architecture skills (dimensional modelling, event-driven, lakehouse patterns)
Comfortable with dbt or equivalent transformation frameworks
Production experience with streaming pipelines on Dataflow/Beam, Flink, or Spark Structured Streaming, ingesting from Kafka and/or Pub/Sub
Experience migrating off legacy warehouses (Snowflake, Redshift, Synapse) onto cloud-native stacks is a plus
Hands-on experience with GCP data services — BigQuery is a must; Pub/Sub, Dataflow, Bigtable, Cloud Composer are strong pluses

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