Technical Program Manager; Data Platform

Technical Program Manager (Data Platform)

Location:

Mountain View, CA / Plano, TX (Hybrid)

We are seeking an experienced Technical Program/Product Manager (TPM) to lead the end-to-end delivery of our modern data platform. This role involves driving multi-team programs focused on designing, building, and scaling a secure, cost-efficient Lakehouse architecture on AWS
.

You’ll work cross-functionally with data engineering, platform, security, and product teams to implement capabilities in Databricks (Delta Lake, Unity Catalog, Workflows/Jobs, Delta Live Tables) and support event-driven data products using AWS Event Bridge
, Kafka
, and Kinesis — across both real-time streaming and batch pipelines.

• Own the program delivery lifecycle for enterprise data platform initiatives.
• Coordinate roadmaps, manage dependencies, and mitigate risks across teams.
• Define and track program metrics, SLAs, and success KPIs.
• Build dashboards and executive reports to communicate program progress and business impact.
• Lead quarterly roadmap planning and prioritization efforts.
• Partner with engineering leads on design decisions, scaling strategy, and cost optimization.
• Manage delivery of new data capabilities in Databricks and event-driven environments.
• Oversee migration efforts from legacy ETL tools (Informatica or equivalent) to modern lakehouse patterns.
• Drive Fin Ops practices to optimize data compute spend.
• Apply AI-native and GenAI-agent product thinking to improve program execution.

• 7+ years of experience in technical program or product management within data platform environments.
• Deep understanding of Databricks, AWS, and event-driven architectures.
• Proven experience managing large-scale, cross-functional programs in Agile settings.
• Hands-on experience with data lakehouse architectures, streaming pipelines, and batch ETL processes.
• Strong executive communication and stakeholder management skills.
• Experience in Informatica or similar enterprise ETL tools.
• Familiarity with AI-native tooling (Builder.io, Cursor, etc.) and modern data ecosystems.
• Ability to prototype, experiment, and drive execution independently.

• Prior experience managing migrations from legacy ETL to Databricks or AWS-based lakehouse systems.
• Exposure to enterprise internal data platforms and Fin Ops cost governance.
• Deep understanding of semantic models, analytical consumption layers, and modern BI tools.

• A combination of technical fluency and delivery excellence.
• The ability to bridge the gap between data engineers, architects, and business stakeholders.
• A forward-thinking mindset — blending data, AI, and product innovation.