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About the Role
- Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and data integration solutions using Databricks, PySpark, and Delta Lake.
- Build and optimize cloud-native lakehouse architectures leveraging Azure Databricks, Azure Data Lake Storage (ADLS Gen2), and modern data engineering best practices.
- Develop robust data ingestion frameworks supporting structured, semi-structured, and unstructured data sources.
- Create high-performance data transformation workflows using Python, SQL, Spark, and Databricks notebooks.
- Design, implement, and optimize data models, schemas, partitioning strategies, and storage structures for large-scale analytics workloads.
- Integrate Databricks environments with downstream platforms including Snowflake, business intelligence tools, APIs, enterprise applications, and reporting solutions.
- Utilize Azure Data Factory (ADF), Azure Functions, and Azure ecosystem services to su...
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