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

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We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.