Job
Core
Design, implement, and industrialize modern lakehouse platforms for clients, focusing on scalable data ingestion, transformation, and analytics enablement.
Role type
Databricks Data Engineer
Builds
Scalable data pipelines and lakehouse architectures on Databricks
Domain
Data Engineering / Cloud Data Platforms
Deliverable
production ML models | product features
Required skills
Databricks, Apache Spark (PySpark/Scala), Delta Lake, SQL, ETL/ELT pipeline development, data modeling (star schema, SCD), cloud data environments (Azure), data quality monitoring
Preferred skills
Unity Catalog, medallion-style architectures, distributed data processing optimization, orchestration patterns
Technologies
Databricks, Apache Spark, Delta Lake, PySpark, Scala, Azure, SQL Server, Oracle, PostgreSQL, Parquet, JSON
Responsibilities
Design and maintain scalable data pipelines and lakehouse architectures; Build and optimize Spark-based ETL/ELT workloads; Implement Delta Lake patterns (bronze/silver/gold layers); Develop robust ingestion patterns from various sources; Create curated data models for analytics and reporting; Apply Databricks engineering best practices; Optimize Spark jobs for performance; Implement data quality and monitoring checks; Collaborate with stakeholders to translate requirements into data products.
Seniority
Mid-level (3–5 years experience), hands-on IC
