• Design and implement complex Spark data logic, focusing on performance optimization, data volume tuning, and robust execution. • Own the architectural design of graph build pipelines, ensuring they are scalable, automated, and highly resilient. • Plan and oversee the strategic re-architecture of data pipelines to meet evolving business needs and scale. • Optimize infrastructure-as-code and schema designs to reduce cloud costs and improve pipeline latency. • Act as a technical consultant for the team, fostering a collaborative and engineer-led approach to design decisions. • Support the development of the engineering team through code reviews, design docs, and architectural best practices. • Ensure the accuracy of mission-critical data outputs.