• Design, develop, and implement robust ETL/ELT data pipelines for large-scale data ingestion, transformation, and storage. • Ensure data quality, integrity, and governance by implementing validation techniques, data monitoring, and automated testing. • Collaborate with cross-functional teams, including data scientists, analysts, platform engineers, and business stakeholders, to develop scalable and reusable data solutions. • Automate deployments and testing using CI/CD pipelines with Git, Terraform, GitHub Actions, or Jenkins. • Design and build custom data tools and abstractions to support analytics, machine learning, and real-time data processing. • Work with DevOps and platform teams to establish efficient deployment and monitoring processes for internal and external data products. • Develop and implement alerting, monitoring, and observability frameworks for data pipelines to ensure reliability and proactive issue resolution. • Contribute to the data architecture and strategy, driving improvements in scalability, performance, and cost optimization. • Stay up to date with emerging technologies and industry best practices to continuously enhance data engineering capabilities.