• Design, build, and scale robust ETL pipelines to support complex data workflows while ensuring high performance, reliability, and adaptability to evolving business needs. • Automate and manage data ingestion from diverse sources (databases, APIs, cloud platforms), ensuring system resilience, fault tolerance, and failover readiness. • Optimize data storage, processing, and retrieval layers to balance performance, scalability, and cost efficiency across the data platform. • Modernize and enhance legacy data systems by identifying gaps, implementing architectural improvements, and aligning solutions with future business requirements. • Lead technical excellence within the data engineering function through mentorship, code reviews, best-practice enforcement, and adoption of advanced tools and frameworks. • Ensure end-to-end data quality, integrity, and governance by implementing validation, monitoring, testing, and compliance-focused data controls. • Collaborate cross-functionally with analytics, product, engineering, DevOps, and business stakeholders to translate requirements into scalable data models and transformations. • Drive a data-driven culture and long-term data strategy by enabling self-service analytics, maintaining clear documentation, leading training initiatives, and contributing to architecture roadmaps and governance policies.