Job Description

Responsibilities
  • Design and implement large-scale Azure and Databricks Data Lakehouse solutions.
  • Build and optimize ETL/ELT pipelines for batch and real-time streaming workloads using Azure Data Factory, Databricks, and Apache Spark.
  • Develop scalable data ingestion frameworks and integrate diverse structured and unstructured data sources.
  • Optimize data storage and query performance using Delta Lake, Parquet format, partitioning, and Spark performance tuning techniques.
  • Implement robust data governance, security, and access control using Unity Catalog, Azure Key Vault, and least-privilege principles.
  • Build and maintain data quality frameworks using Great Expectations or similar validation tools for batch and streaming data.
  • Automate pipeline deployment and CI/CD processes using Azure DevOps, Git, and configuration management tools.
  • Enable advanced analytics and ML workflows by preparing curated datasets and in...

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