Design and develop scalable Lakehouse architectures that enable high-performance data ingestion, processing, and analytics.
Define and enforce best practices for ETL, data modeling, and data governance within the Azure ecosystem.
Architect and optimize Medallion Architecture (Bronze, Silver, Gold) for efficient data transformation and analytics.
Ensure high availability, security, and performance of Azure Databricks environments.
Define data infrastructure strategies, ensuring alignment with business objectives and scalability requirements.
Technical Leadership & Development:
Provide architectural guidance and hands-on development support for ETL pipelines, batch & streaming solutions in Azure Databricks using PySpark and SQL.
Drive the implementation of Data Vault, Star Schema, and Data Warehouse modeling techniques.
Implement CI/CD pipelines, version control, and automation to streamline deployment and testing.
Lead the integration of Azure Data Services such as Azure Data Factory, Azure Synapse, Delta Lake, and Delta Live Tables.
Apply Chaos Engineering practices to ensure system resilience and fault tolerance.
Collaboration & Mentorship:
Work closely with Product Owners, Data Engineers, Data Scientists, and Business Analysts to deliver high-quality data solutions.
Provide technical mentorship to engineering teams, enabling them to follow best practices in Databricks development, ETL, and data pipeline management.
Collaborate across departments to design functional and scalable solutions that balance business needs and technical feasibility.
Analytics & Optimization:
Conduct performance tuning and optimization of Databricks workloads, Spark jobs, and SQL queries.
Define and implement monitoring frameworks to track data quality, lineage, and processing performance.
Design efficient data governance, access control, and security policies for Databricks and Azure environments.
Lead root-cause analysis and problem-solving for complex data engineering challenges.