Ezcaterinc

Senior Product Manager, Data Platform (Remote)

Boston, MA · Senior

Sponsorship not specified$161k-$213kDetected 8 days ago

SQLPlatform EngineeringData EngineeringProduct ManagementProduct StrategyStakeholder ManagementCommunication

About the role

For workplaces, ezCater provides flexible and scalable solutions for everything from employee meal programs to one-off meetings, all backed by 24/7 service and business-grade reliability.
Your first major focus is our Enterprise Data Hub: consolidating fragmented, legacy data into governed, business-ready data products; driving their adoption; and sunsetting the legacy environment they replace.
Ensure the same foundation meets machine-learning and data-science needs - reliable data access, performance, and monitoring. - Migration and legacy sunset.

Responsibilities

Own the definition of what makes a data product trusted and production-ready: classification and protection of sensitive information, role-based access aligned to classification, validation and contracts between raw and refined layers, a governed semantic and metrics layer, and a catalog that makes data products discoverable with clear ownership, lineage, and definitions.
Own how platform capabilities surface for the people who use them: governed self-service, business intelligence, and AI and natural-language experiences grounded on trusted data.
Lead the move from the legacy environment onto the platform: reconcile the most depended-on legacy data against trusted sources, plan and resource the cutover with each business area (including user-acceptance testing and the refactoring of downstream reporting), and sunset legacy - recognizing that some legacy will run in parallel during the transition.
Drive credible, dated commitments and milestone-level goals rather than open-ended task lists, make trade-offs across value, effort, risk, and timing explicit, and keep dependencies and risks visible in integrated plans.
Validate data products against real usage with their business owners before build, drive adoption and change management, own documentation and enablement, measure business impact, and adjust the roadmap accordingly.
Raise the bar for data-platform product management: enable data product managers and partners to define products against the architecture, evolve platform product practices, and mentor others to "think in products."
Deep familiarity with modern cloud data-warehouse and lakehouse architectures, data lakes, and ELT and transformation patterns, and with modeling frameworks and semantic and metrics layers that can support AI and natural-language analytics.
Strong SQL and the comfort to explore data and platform metadata - logs, cost, usage - and data-observability signals yourself, to validate requirements, debug issues, and size opportunities.
Proven ability to build and execute multi-quarter, multi-team plans, and to make and communicate trade-offs across competing initiatives; solid delivery discipline in an agile environment, including tracking progress against estimates and velocity.
The company makes it easy for any organization to manage its food needs and order from over 125,000 restaurants nationwide.

Nice to have

Designing and evaluating natural-language analytics flows - grounding answers in governed data and measuring quality, latency, and trust.
Familiarity with modern AI-powered data-platform patterns (semantic layers, retrieval and search, conversational analytics, or agentic workflows) and how they reset expectations for how people discover and consume data.
Experience sunsetting a legacy data environment in favor of a governed platform, including reconciliation and parallel-run cutovers.
Please note: Final offer amounts are determined by multiple factors, including prior experience, expertise and region & may vary from the amount above.
5+ years working in or directly with data engineering, data platform, or analytics teams, ideally in complex, multi-system environments.
5+ years owning data or analytics products, with direct data-product-management experience strongly preferred
experience owning platform- or infrastructure-adjacent data products is a plus.
Experience with business-intelligence and self-service analytics tools and how they consume data from a platform, including governance, performance, cost, and how they participate in AI and natural-language analytics.

Skills

Migration and legacy sunset.

Compensation

The national total target cash compensation range for this position, including base salary and bonus target, is $161,000–$213,000 annually.*

Benefits

You will own the long-term vision, strategy, and multi-quarter roadmap for the platform, and you will own it end to end: not only the underlying capabilities, but how they show up for the people who consume them.
Own platform health as a product promise - freshness and success service levels, availability, and fast detection and resolution of data incidents through strong observability.
Platform product strategy and vision.
Define and continuously refine the platform's vision and product strategy, grounded in company and Enterprise Data goals, and connect it to the broader data and company roadmaps.
Account for machine-learning and data-science workloads as part of the overall strategy, so the same foundation serves them without forcing parallel, ungoverned pipelines.
Ensure the same foundation meets machine-learning and data-science needs - reliable data access, performance, and monitoring.
Familiarity partnering with data-science and machine-learning teams and supporting their needs on a shared platform (data access, performance, and monitoring).
A disposition that is friendly, flexible, pragmatic, and curious, with a desire to learn something new every day and to raise the bar for the broader data, platform, and product teams.

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This listing is sourced directly from Ezcaterinc's careers page and normalized into a canonical job model.