Manager of Data Platform Engineering

The Manager, Data Platform Engineering, is responsible for leading, developing, and organizing a high-performing team of data platform engineers. You will own the people, process, and delivery health of your team — ensuring engineers are growing in their careers, teams are delivering reliably, and the platform function is well-coordinated with the broader organization. This is a first-line management role that sits at the intersection of technical credibility and people leadership, you must possess sufficient technical depth to earn trust, participate meaningfully in architectural conversations, remove engineering blockers, and make informed decisions about resourcing and prioritization. You will partner closely with the Lead Data Platform Engineer to ensure alignment between technical direction and team execution. While the Lead owns architecture and standards, you own: hiring, career development, performance, team health, and delivery operations. Together, you form the leadership unit for the Data Platform function. This role is ideal for a seasoned senior engineer who has made the deliberate choice to grow into engineering leadership, or an experienced engineering manager who wants to operate in the dynamic, high-impact world of data infrastructure. Key Responsibilities People Leadership & Team Development 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 Hiring & Organizational Design 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. Delivery Operations & Program Management 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. Technical Partnership & Credibility 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. Stakeholder Management & Organizational Influence 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 team. Contribute to shaping the engineering culture and management practices across the broader engineering organization — share what works, contribute to manager forums, and help raise the bar on people leadership. 8-13 years of total professional experience in software or data engineering, with at least 1-2 years in an engineering management role with direct reports. Demonstrated ability to recruit, develop, and retain engineering talent across levels; track record of building high-performing, cohesive teams. Proven experience delivering complex technical programs on time — able to manage scope, risk, dependencies, and stakeholder expectations across multiple concurrent workstreams. Sufficient technical depth in data engineering to earn team trust: experience with data pipelines, cloud data infrastructure, and distributed systems. Strong command of engineering management fundamentals: 1:1s, performance reviews, goal-setting, career development frameworks, and compensation discussions. Excellent communication skills — written and verbal — with the ability to tailor messaging for engineers, technical peers, and senior non-technical leadership alike. Experience running agile delivery processes (Scrum, Kanban, or hybrid) and maintaining team-level metrics that inform planning and forecasting. Demonstrated ability to navigate ambiguity, make decisions with incomplete information, and maintain team direction and morale in periods of organizational change. Self-aware, empathetic, direct, and skilled at giving feedback that is candid, kind, and growth-oriented. Preferred Qualifications Prior hands-on experience as a data platform or data infrastructure engineer; deep familiarity with the technical landscape your team operates in (Spark, Airflow, Snowflake, Kafka, dbt, etc.). Experience managing engineers in a platform-as-a-product or internal developer platform context, where the team's customers are other engineering teams. Background leading teams through significant technical transformation programs — cloud migrations, architecture re-platforms, or tooling overhauls. Experience building and scaling engineering teams in a high-growth environment, including rapid hiring, onboarding, and org design iterations. Familiarity with engineering leveling frameworks and the ability to calibrate performance and promotion decisions consistently across a team. Exposure to data governance, compliance, or regulatory requirements (GDPR, CCPA, HIPAA) that affect platform design and operations.

Education:

Minimum of a HS Diploma or GED Bachelors preferred