• Responsible for selecting and enabling cloud platforms, data platforms, tools, and tech stacks by collaborating with leadership, legal, procurement, and vendors to align with organizational goals.

• Established a scalable enterprise data platform for analytics and reporting, defining robust architecture, reusable patterns, and promoting strong engineering principles.

• Designed and implemented frameworks for data ingestion, transformation, and quality assurance, ensuring reliable and efficient data pipelines.

• Developed reference pipelines and reusable patterns leveraging Databricks, AWS, and Airflow orchestration to support diverse organizational use cases.

• Partnered with business and product managers to define and deliver a strategic product roadmap.

• Architected and delivered marketplace data products for enterprise analytics and reporting, enabling impactful insights and accessibility.

• Orchestrated complex data and machine learning pipelines to support a wide range of enterprise metrics, enhancing operational efficiency and decision-making accuracy.

• Provided expert consulting to analytics and data science teams for data and platform optimization.

• Established and enforced data engineering practices, including code reviews, documentation standards, and robust support processes.

• Facilitated a Community of Practice (CoP) for data engineering teams across the enterprise, conducting training sessions and mentoring engineers at various levels to drive innovation and collaboration.

• Led the migration of on-premise data warehouses to a modern, cloud-based data platform, ensuring scalability, efficiency, and alignment with business goals.

• Architected, designed, and implemented the migration of the Customer 360 dataset to a cloud data platform, handling large-scale data and complex machine learning pipelines.

• Designed and executed the migration of numerous ML models, including Point-to-Buy (PtB), prospect, and client segmentation models, to Databricks as part of the platform modernization efforts.

• Developed and implemented CI/CD pipelines for deploying data and ML workflows on the data platform using Bamboo, GitHub, and Bitbucket, streamlining deployment processes.

• Conducted evaluations of multiple data platforms (AWS, Databricks), ingestion tools (StreamSets, Talend, Informatica), and transformation tools to select the best solutions for building a modern enterprise data platform.