Technical Program Manager (Data Platform)

Regent Strategic Solutions Inc.; Plano (TX); Hybrid; USD 120,000 - 150,000; Full time

Job summary

A leading technology firm is seeking a Technical Program Manager for their data platform team. This role requires over 7 years of experience in program management, focusing on delivering a modern data platform using AWS and Databricks. Key responsibilities include managing cross-functional teams, defining program metrics, and driving migration efforts from legacy ETL tools to advanced data lakehouse architectures. The ideal candidate will have strong technical skills and the ability to communicate effectively with stakeholders.

Qualifications

• 7+ years of experience in technical program or product management within data platforms.
• Deep understanding of Databricks, AWS, and event-driven architectures.
• Hands-on experience with data lakehouse architectures, streaming pipelines, and batch ETL processes.

Responsibilities

• 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.

Skills

Technical program management

Communication

Stakeholder management

Agile methodologies

Data lakehouse architecture

Event-driven architecture

AWS

Databricks

Tools

Databricks

Informatica

AWS EventBridge

Kafka

Kinesis

Job description

Technical Program Manager (Data Platform)

Location: Mountain View, CA / Plano, TX (Hybrid)

About the Role

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 EventBridge, Kafka, and Kinesis — across both real-time streaming and batch pipelines.

Key Responsibilities

• 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 FinOps practices to optimize data compute spend.
• Apply AI-native and GenAI-agent product thinking to improve program execution.

Required Skills & Experience

• 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.

Preferred Qualifications

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

What You’ll Bring

• 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.