• Design and build data pipelines • Develop, maintain, and optimize ETL/ELT pipelines on Databricks and Spark. • Integrate data from multiple internal and external sources into a centralized data platform. • Own data modeling & architecture • Design and maintain robust data models (e.g., star/snowflake schemas, data vault, dimensional models) to support analytics and self-service BI. • Establish and enforce data modeling standards and documentation. • Ensure data quality, reliability, and performance • Implement data quality checks, validation frameworks, and monitoring. • Tune queries and jobs for performance and cost efficiency in Databricks and downstream systems. • Collaborate and lead • Partner with data analysts, data scientists, and product/engineering teams to understand data needs and translate them into technical solutions. • Provide technical leadership and mentorship to other data engineers; help review designs and code. • Governance & best practices • Contribute to and refine our data governance, security, and access control practices. • Drive best practices around version control, CI/CD for data, and code standards.