Role & responsibilities :
- Design, develop, and maintain end-to-end data pipelines using Azure Databricks and Azure Data services
- Build scalable and productive ETL/ELT workflows using Python, PySpark, and SQL
- Integrate data from multiple sources (structured and unstructured) into data platforms
- Optimize data processing performance and ensure data quality, reliability, and consistency
- Develop and maintain data models to support analytics and reporting requirements
- Create and manage interactive dashboards and reports using Power BI, Azure Databricks
- Collaborate with business stakeholders to understand data requirements and deliver actionable insights
- Work closely with cross-functional teams (Data Ops, Architects, DevOps)
- Focuses on end-to-end strategy, AI/ML integration, and regulatory reporting capabilities.
- Business & Compliance: Regulatory Reporting,, BI, AI, ML Models.





Preferred candidate profile
- Strong experience with Azure Databricks and distributed data processing
- Proficiency in Python for data engineering tasks
- Hands-on experience with Azure Data Services (ADF, ADLS, Synapse, etc.)
- Expertise in SQL and database concepts.
- Solid experience in Power BI development, data modeling, and dashboard creation ,Databricks dashboard creation.
- Good understanding of data warehousing concepts (Star schema, Snowflake schema)
- Experience in handling large-scale data processing and performance tuning
- Familiarity with version control tools (e.g., Git) and CI/CD pipelines
- Strong analytical and problem-solving skills

📌 Data Engineer Lead (Mumbai)
🏢 SKILLVENTORY
📍 Mumbai