Data Engineer
Job Summary
Hands-on and detail-driven, the full-time Data Engineer will build and scale a modern data platform, developing reliable data pipelines and systems while collaborating with cross-functional teams in a hybrid work environment.
Key responsibilities
- Build and maintain scalable data pipelines (batch and streaming) using Databricks, Spark, Kafka, and AWS services
- Design, develop, and optimize ETL/ELT workflows using DBT, PySpark, and SQL
- Collaborate with Finance and marketing teams to enable data use cases and support AI-driven applications
Required qualifications
- 6+ years of experience in data engineering or a related field
- Strong hands-on experience with Databricks, AWS (S3, Glue, Athena, EMR), and Kafka
- Proficiency in Python (PySpark) and SQL for large-scale data processing
- Experience building and maintaining ETL/ELT pipelines with tools like DBT or Airflow
- Familiarity with reverse ETL/data activation workflows and syncing data to tools like Salesforce and HubSpot
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