Data Engineer
Key responsibilities:**
- Design and build the Apache Spark/PySpark ETL pipeline (Bronze → Silver → Gold medallion architecture)
- Implement Apache Iceberg table operations (MERGE, UPSERT, SCD Type 2 logic, incremental loads)
- Design and validate the analytical star schema (fact/dimension tables, conformed dimensions)
- Define and execute three-tier data quality rules, dead-letter handling, and validation logic
- Build business logic connectors, transformation helpers, and custom derivations
- Collaborate with stakeholders to clarify KPIs, query patterns, and analytical use cases
- Write comprehensive unit, integration, and end-to-end tests
**Required skills:**
- 5+ years data engineering, backend development, or full-stack analytics platform work
- Expert-level PySpark, SQL, and cloud data warehousing (Snowflake/Databricks/similar)
- Apache Iceberg or strong willingness to learn advanced table formats
- Dimensional modelling fundamentals (Kimball star schema, slowly changing dimensions)
- Python for data transformation and microservices
- API design, error handling, and testing discipline
Required skills:**
- 5+ years data engineering, backend development, or full-stack analytics platform work
- Expert-level PySpark, SQL, and cloud data warehousing (Snowflake/Databricks/similar)
- Apache Iceberg or strong willingness to learn advanced table formats
- Dimensional modelling fundamentals (Kimball star schema, slowly changing dimensions)
- Python for data transformation and microservices
- API design, error handling, and testing discipline
Required skills:**
- 5+ years data engineering, backend development, or full-stack analytics platform work
- Expert-level PySpark, SQL, and cloud data warehousing (Snowflake/Databricks/similar)
- Apache Iceberg or strong willingness to learn advanced table formats
- Dimensional modelling fundamentals (Kimball star schema, slowly changing dimensions)
- Python for data transformation and microservices
- API design, error handling, and testing discipline
EXL
Photon