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Design, build, and optimize ETL pipelines and data infrastructure on AWS (EMR, S3, DynamoDB). Develop orchestration with Airflow, implement Spark/PySpark data processing, ensure data quality and governance, collaborate with data science on entity resolution and analytical tooling, and produce monitoring and documentation.

Own product roadmap and lead a cross-functional Scrum team to build B2C and B2B data-powered products. Discover opportunities, create PRDs and user stories, prioritize features, drive launches, measure impact, and iterate using data, user research, and stakeholder alignment.

Lead and manage a data engineering team to design, build, and operate scalable data pipelines, ETL, data warehouses/lakes, and reporting on AWS/Azure. Drive data governance, quality, SLA definitions, automation, and cross-functional collaboration with data scientists, analysts, and product owners to deliver analytics solutions.

Act as the technical partner for sales: lead discovery, deliver tailored demos and POCs, design solutions, answer security/integration questions, contribute to RFPs, and enable sales teams.

Lead data product strategy and backlog as Scrum Product Owner to ingest, clean, and aggregate people data. Define data quality, acceptance criteria, and entity resolution improvements, collaborate with data science and engineering, evaluate vendors, and drive batch append and identity graph product enhancements.