• Design, build, and maintain scalable data pipelines using Python, Apache Airflow, and Apache Spark • Analyze business and technical requirements and translate them into reliable, future-proof data solutions • Develop, validate, deploy, and support complex ETL/ELT pipelines at scale • Build clean, secure, and maintainable REST APIs following company standards • Implement real-time and batch processing solutions for diverse data sources • Develop reusable data engineering and AI frameworks for enterprise-wide adoption • Define and manage domain-based “source of truth” data models, ensuring scalability and end-to-end data lineage • Implement data governance practices, automate data quality checks, and enable pipeline testing • Optimize data infrastructure for performance, cost efficiency, and reliability • Manage source control, CI/CD pipelines, and production deployments • Partner with data scientists and analysts to support AI/ML initiatives