Job Summary (List Format):

- Design, develop, and optimize scalable ETL/ELT pipelines using Azure Databricks (PySpark/Spark SQL).
- Build and maintain robust Delta Lake data architectures following industry best practices.
- Develop and tune complex SQL queries, stored procedures, and scripts on SQL Server.
- Handle large-scale data ingestion, transformation, and processing with high performance and reliability.
- Develop and maintain Power BI dashboards, datasets, and semantic models for analytics and reporting.
- Implement data modeling best practices, including star schemas, fact and dimension tables, and SCD.
- Collaborate with business and analytics teams to translate requirements into scalable technical solutions.
- Contribute to the architecture of end-to-end Azure data platform solutions.
- Ensure data quality, governance, security, and compliance throughout data pipelines.
- Optimize Databricks clusters, jobs, and workflows for performance and cost efficiency.




- Utilize advanced skills in Azure Databricks, SQL Server (including query optimization), and Power BI.
- Apply solid experience in ETL/ELT pipelines, distributed data processing, and BI/data warehousing architecture.
- (Preferred) Work with Azure Data Factory, Azure Synapse Analytics, and CI/CD pipelines (Azure DevOps/Git).
- (Preferred) Exposure to data testing, validation frameworks, and data governance/security best practices.
- Demonstrate strong analytical, problem-solving, communication, and stakeholder management skills.
- Work independently and collaboratively within cross-functional teams.
- Maintain strong documentation and design articulation abilities.
- Exhibit a proactive mindset focused on quality, scalability, and continuous improvement.

📌 Azure DataBricks Engineer (India)
🏢 Sparix Global
📍 India