Data Engineering Analytics Lead

We are looking for a strong Data Engineering Analytics professional with 10 years of experience in building data pipelines, data models and analytics solutions, with hands-on expertise in Databricks, SQL, PySpark, Python and Power BI. Work Timing -9 00 am-6 00 pm/ 6 30 PM - 3 30 AM Responsibilities include Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, Python, and Azure Data Factory. Build and optimize enterprise-grade data solutions using Databricks Lakehouse architecture and Delta Lake. Develop high-performance data transformation workflows and implement data quality controls. Create and maintain logical and physical data models to support reporting, analytics, and business intelligence requirements. Write and optimize complex SQL queries, stored procedures, views, and data transformation logic. Design and implement Medallion Architecture (Bronze, Silver, Gold layers) for modern analytics platforms. Develop interactive dashboards, reports, and analytical solutions using Power BI. Collaborate with business stakeholders to understand reporting and analytics requirements. Ensure data governance, metadata management, and data cataloging best practices are followed. Implement performance optimization strategies across data pipelines, Databricks workloads, and reporting solutions. Leverage AI/LLM-enabled tools for data analysis, insight generation, and analytics acceleration. Work closely with cross-functional teams including Data Architects, Business Analysts, and Product Owners. Support CI/CD and version control practices for data engineering solutions.