Manager of Data Platform Engineering

Job Description

• Directly manage 4-5 data platform engineers across levels (Engineer I through Senior Engineer III); serve as their primary advocate, coach, and career guide.
• Conduct regular 1:1s with each direct report focused on growth, blockers, wellbeing, and career trajectory.
• Own the career development plans for each team member; set clear expectations at every level, identify growth opportunities, and provide timely, actionable feedback.
• Drive performance management end-to-end: set goals, provide continuous feedback.
• Identify high-potential engineers and create stretch opportunities that accelerate their development toward the next level.
• Foster a team culture of psychological safety, inclusion, continuous learning, and high accountability – where engineers feel empowered to take initiative and safe to raise concerns.
• Address performance gaps early and constructively.

• Own the full recruitment lifecycle for your team: define headcount needs, write and refine job descriptions, run structured interview processes, and make hiring decisions.
• Partner with recruiting to build and maintain a healthy pipeline of engineering talent at all levels; actively source candidates and represent the company at recruiting events.
• Onboard new hires effectively: ensure they have a structured ramp plan, a buddy/mentor, and clear 30/60/90-day expectations from day one.

• Own the health of the team's delivery system: sprint cadence, backlog grooming, capacity planning, dependency management, and release coordination.
• Ensure the team consistently delivers against commitments; proactively identify risks, surface blockers early, and create conditions for engineers to do their best work.
• Establish and maintain clear team-level SLAs, on-call rotations, and incident response processes; hold the team accountable to reliability standards.
• Drive quarterly planning in coordination with the Lead Engineer and Director: translate organizational priorities into team-level goals, milestones, and resourcing decisions.
• Manage cross-team dependencies with partner engineering organizations (ML, Analytics); ensure alignment and resolve conflicts at the manager level.
• Own team-level reporting and status communication to leadership: weekly/bi-weekly updates, risk flags, and delivery summaries that give stakeholders accurate, timely visibility.

• Maintain sufficient technical depth to participate in architectural discussions, evaluate engineering trade-offs, assess estimates, and identify when the team is over- or under-resourced for a given problem.
• Partner closely with the Lead Data Platform Engineer to ensure technical direction is translated into executable work; bridge the gap between architectural vision and sprint-level delivery.
• Represent technical considerations in cross-functional conversations – with infrastructure, Data Science, Analytics, and Directors – and advocate for necessary infrastructure investment.
• Contribute to technical decisions where your perspective as a manager is valuable: team ergonomics, tooling adoption, process improvements, and build-vs-buy trade-offs with organizational implications.
• Stay current with data platform trends and adjacent technologies to have informed conversations with your team and with engineering leadership about the evolving landscape.

• Serve as the primary point of contact for partner Information Systems & Services (ISS) managers, and business stakeholders on matters of team delivery, capacity, and roadmap alignment.
• Represent the Data Platform Engineering team in cross-functional planning forums, leadership reviews, and all-hands; communicate team accomplishments, challenges, and needs clearly.
• Proactively build relationships with peer managers across the organization to improve cross-team collaboration, reduce friction, and identify shared investment opportunities.
• Partner with the Executive Director on budget planning, headcount justification, and tooling procurement decisions that affect the…