Responsibilities
- Create and manage data workflows using Azure Databricks for reliable data processing
- Develop and refine data transformations using PySpark and SQL within Databricks environments
- Build and sustain Lakehouse frameworks leveraging Delta Lake technology
- Construct ETL and ELT workflows coordinated through Azure Data Factory
- Consolidate data from diverse sources into unified data platforms and analytical layers
- Design and manage data models and warehouse schemas to support analytics needs
- Ensure high data quality, system scalability, and efficient performance across large data pipelines
- Work closely with BI teams to enable Power BI integrations and reporting solutions
- Maintain and enhance legacy SQL Server platforms and SSIS-based ETL systems as needed
- Support the development of modern, cloud-native data architecture strategies
Compensation
Competitive salary based on experience
Work Arrangement
Hybrid or remote options available
Team
Collaborative team focused on cloud data solutions and innovation
Responsibilities
- Design, develop, and maintain data pipelines using Azure Databricks
- Build and optimize data transformations using PySpark and SQL in Databricks
- Implement and maintain Lakehouse architectures using Delta Lake
- Develop ETL/ELT pipelines orchestrated through Azure Data Factory
- Integrate data from multiple sources into the data platform and analytical layers
- Design and maintain data models and data warehouse structures for analytics
- Ensure data quality, scalability, and performance of large-scale data processing pipelines
- Collaborate with BI teams to support Power BI and reporting platforms
- Support and evolve existing SQL Server data platforms and ETL solutions (SSIS) when required
- Contribute to the design of modern cloud-based data architectures
Not specified
