Technical Program Manager

About the Role

Key Responsibilities

• Drive execution of end-to-end data programs, ensuring timelines, milestones, and quality targets are met.
• Develop project plans, track progress, proactively identify risks, and drive resolution of blockers across teams.
• Coordinate program activities across agile squads involving data engineering, ML, analytics, architecture, and infrastructure teams.
• Communicate program status via regular updates to key stakeholders.
• Make informed, timely decisions by balancing short-term execution needs with long-term strategic impact.
• Partner with technical and non-technical teams including product, analytics, engineering, and business operations to align on scope, success criteria, and timelines.
• Serve as a liaison between stakeholders, ensuring clear communication and translating business requirements into actionable technical plans.
• Support intake and prioritization of new data initiatives, working with leadership and PMs to define roadmaps and OKRs.
• Implement established best practices for data program delivery, including documentation, program status reporting, backlog grooming, agile ceremonies, and release coordination.
• Maintain visibility into key metrics such as delivery velocity, data product SLAs, model performance, and business impact.
• Contribute to the implementation of governance and compliance processes in partnership with Data Governance.
• Foster a positive, inclusive team culture by actively participating in team rituals, supporting onboarding, and promoting knowledge sharing.

Requirements

• 2-5 years of experience in technical program management, preferably in data engineering, ML, analytics, or platform environments.
• Proven ability to manage technical programs end-to-end across multiple teams and stakeholders.
• Familiarity with data pipelines, ETL/ELT, data warehousing, analytics tooling (e.g., dbt, Looker, Snowflake), and ML lifecycle concepts.
• Strong organizational and communication skills with the ability to distill complexity and manage competing priorities.
• Experience with agile methodologies, program planning tools (Jira, Asana, Confluence), and stakeholder reporting.
• Bachelor's degree in computer science, Engineering, Data, or a related field, or equivalent practical experience.
• Experience working within modern data stacks and platforms (e.g., Databricks, Airflow, Spark, Kafka).
• Familiarity with MLOps workflows and model governance practices.
• Understanding of data privacy, compliance (e.g., GDPR, HIPAA), or security in a data context.
• Background in data-intensive product or platform organizations.

Nice to Have

• Experience with data pipelines, ETL/ELT, data warehousing, and analytics tooling.
• Knowledge of MLOps workflows and model governance.
• Experience with modern data platforms such as Databricks, Airflow, Spark, Kafka.

Benefits & Perks

• Health plans including options as low as $0 per paycheck, with programs for fertility, family planning, mental health, and fitness.
• Generous paid time off (PTO & sick leave).
• Annual bonus and long-term incentive opportunities based on performance.
• 401k with up to a 5% match.
• Commuter benefits, pet insurance, and more.
• Salary range: $116,000 - $145,000 USD, dependent on experience, location, and market demand.
• Additional benefits include medical, vision, dental insurance, life insurance, disability insurance, and participation in stock or cash bonus programs.
• Paid personal time off and 14 paid company holidays.
• Paid sick time in accordance with applicable laws.