Data Engineer
Summary
Designs and builds data pipelines, processes workflows, and ensures data accuracy for analytics and business intelligence, using Databricks, PySpark, and cloud platforms.
Data Engineers design and build data systems and pipelines. Responsibilities include developing data processing workflows, optimizing data storage, and ensuring data accuracy. You will collaborate with data scientists and analysts to meet data requirements and resolve data issues. Strong experience in data engineering and problem-solving skills are required.
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Required Skills Databricks
- Databricks Workspace
- Databricks Jobs & Workflows
- Delta Lake
- Delta Live Tables (DLT)
- Unity Catalog
- Databricks SQL
- MLflow (preferred)
- PySpark
- Python
- SQL
- Spark SQL
- ETL / ELT Design
- Data Warehousing
- Data Lakes
- Batch Processing
- Real-Time Streaming
- Data Modeling
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Git
- Azure DevOps / Jenkins / GitHub Actions
- Airflow (preferred)
- Kafka/Event Hub (preferred)
Bachelor's/Master's in Engineering 2-5 years