• Design, build, and operate scalable batch and streaming data pipelines • Develop and orchestrate workflows using Apache Airflow • Implement transformations and analytics-ready datasets using DBT • Build and maintain real-time pipelines using Kafka • Leverage Databricks for data processing, analytics, and AI enablement • Support AI and GenAI use cases, including enabling high-quality data access for tools like Databricks Genie • Design and optimize data storage using Apache Iceberg and Lakehouse architecture • Ingest and manage data from diverse internal and external sources using Fivetran • Handle a wide variety of data structures (structured, semi-structured, and event-based data) • Build and maintain a semantic layer that enables trusted reporting and self-service analytics • Implement data quality frameworks, monitoring, and unit test automation to ensure reliability at scale • Partner with BI, product, and engineering teams to deliver data that is intuitive, trusted, and actionable • Optimize performance, scalability, and cost across AWS services such as Athena, EC2, and related tooling • Contribute to data platform standards, documentation, and best practices