Design and maintain scalable batch and real-time data pipelines, ETL/ELT workflows, and cloud-native data platforms. Build data lake, warehouse, and lakehouse architectures; implement quality, monitoring, security, and governance standards; and optimize performance and costs. Collaborate with stakeholders, analytics, BI, and AI teams to deliver trusted datasets. Participate in architecture reviews, code reviews, sprint planning, mentoring, documentation, tool evaluation, and proof-of-concept initiatives.

Lead architecture and delivery of Databricks-based data platforms for US clients. Build medallion architectures, Delta Lake pipelines, governance, orchestration, and production PySpark and SQL solutions. Establish engineering standards for testing, CI/CD, infrastructure as code, monitoring, and quality. Lead a team of 3–5 data engineers, mentor staff, conduct reviews, support hiring, and serve as the technical client contact. Contribute to pre-sales, internal accelerators, reference architectures, delivery playbooks, and technical content.