What's included

• Optimized Data Pipelines

  End-to-end data ingestion, transformation, and loading pipelines using Apache Spark and Databricks. Scalable pipelines for both batch and streaming data to handle diverse data sources.

• Medallion Architecture Implementation

  A modular architecture with Bronze (raw), Silver (cleaned), and Gold (aggregated) layers for data processing. Designed for traceability, data quality, and analytics-readiness.

• Delta Lake Integration

  Implementation of Delta Lake for data versioning, ACID transactions, and efficient handling of big data in Databricks.

• Real-Time and Batch Processing

  Real-time data pipelines with tools like Databricks Autoloader and structured streaming. Batch pipelines for historical or large-volume data

• Cost-Optimized Solutions

  Cost-efficient Spark and Databricks jobs with fine-tuned cluster configurations and resource allocation. Can make use of shared cluster, job cluster, serverless compute, spot instances. Databricks suggested approaches.

• Data Governance and Quality Frameworks

  Implementation of data validation checks, monitoring, and alerting for pipeline failures. Enforcing security, access controls, and compliance with client-specific regulations.