Senior Data Product Manager, Delivery & Fulfillment

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Product Manager, Delivery & Fulfillment based in the United States.

This is a senior product leadership role focused on building the data foundation that powers delivery and fulfillment operations at scale.
You will turn a complex, multi-system operational domain into a trusted, extensible data product used across the organization.
Your scope will span canonical data models, metrics architecture, governed data products, telemetry, and decision-making signals.
You will work closely with engineering, architecture, operations, analytics, and data science teams to establish a shared foundation.
The role offers the opportunity to build a new data capability from the ground up while influencing intelligent routing, risk, and service-level decisions.
You will own the product vision, priorities, adoption, reliability, and measurable business outcomes while engineering owns implementation.
This is an environment where strong product thinking, technical depth, and cross-functional leadership directly shape how data creates business value.

\n

Accountabilities:

As the Senior Data Product Manager, you will own the fulfillment data domain as a strategic product, ensuring it is trusted, scalable, governed, and valuable to its users.

• Define and continuously evolve the vision, strategy, roadmap, and success metrics for the fulfillment data domain.
• Own the canonical fulfillment lifecycle model, including events, entities, relationships, and standard, alternate, and exception paths.
• Establish and maintain the metrics architecture across operational, geographic, capability, coverage, and performance dimensions.
• Define what makes data products trusted and production-ready, and lead the delivery of critical analytics and platform data products.
• Design data products for multiple consumption paths, including self-service analytics, direct querying, telemetry, and model-driven signals.
• Ensure the data foundation reliably supports machine learning and decisioning use cases such as intelligent routing, pickup-time prediction, risk scoring, and service-level differentiation.
• Define the signals, telemetry, feedback loops, and data contracts required by downstream models and decisioning systems.
• Break complex initiatives into manageable, estimable data-product units and establish clear milestones, commitments, dependencies, and delivery plans.
• Balance business value, effort, risk, timing, and cost while maintaining visibility into project dependencies and delivery risks.
• Establish strong expectations for data freshness, accuracy, reliability, observability, and incident resolution.
• Monitor the cost and unit economics associated with the data products and capabilities being developed.
• Validate data products with business owners before and after launch, drive adoption and change management, and measure business impact.
• Own documentation, enablement, and ongoing improvements based on user feedback and measurable outcomes.
• Partner with the broader enterprise data platform to leverage shared governance, cataloging, semantic layers, and data infrastructure rather than creating parallel solutions.
• Serve as the connective point between engineering, architecture, delivery operations, analytics, product leadership, and business stakeholders.
• Act as the authoritative product expert for the fulfillment data domain, including its models, capabilities, constraints, and data flows.

Requirements:

The ideal candidate combines strong data product management experience with enough technical depth to work confidently across modern data platforms, analytics, machine learning, and complex operational environments.

• 7+ years of experience working in or closely with data engineering, data platform, analytics, or data product teams, ideally in complex multi-system environments.
• 5+ years of experience owning data or analytics products, with direct data product management experience strongly preferred.
• Proven success taking data products from discovery and requirements through launch, adoption, and measurable business impact.
• Experience building shared or foundational data assets and defining data domains from the ground up.
• Strong knowledge of canonical and domain modeling, event and entity design, and metrics or KPI architectures.
• Deep familiarity with modern cloud data warehouses and lakehouse architectures, ELT and transformation patterns, modeling frameworks, semantic layers, and metrics platforms.
• Strong SQL skills and the ability to independently explore data and metadata to assess usage, quality, lineage, costs, requirements, and opportunities.
• Experience partnering with data science and machine learning teams on reliable data access, signals, features, performance, and monitoring.
• Working knowledge of data governance, classification, access controls, data quality, and observability practices.
• Proven ability to develop and execute multi-quarter, multi-team strategies and communicate trade-offs across competing priorities.
• Strong delivery discipline, including estimation, milestone tracking, dependency management, and progress reporting.
• Excellent communication and stakeholder management skills, with the ability to explain complex data concepts to non-technical audiences and influence senior leaders.
• Comfortable collaborating across engineering, architecture, operations, analytics, product, and business teams.
• Friendly, flexible, pragmatic, and curious approach, with a willingness to continuously learn and raise the bar for data, platform, and product teams.
• Ability to travel up to 5 days per quarter for team gatherings, Together Weeks, and other applicable events.
• Experience in logistics, last-mile delivery, marketplaces, food, or fulfillment is a plus.
• Experience building data foundations for routing, risk scoring, forecasting, recommendation, or other decisioning systems is a plus.
• Familiarity with AI-powered data platform patterns, including semantic layers, retrieval and search, and conversational analytics, is a plus.
• Experience building on or migrating to a governed enterprise data platform and semantic layer is a plus.
• Must have unrestricted authorization to work for any employer in the United States; sponsorship for work visas or permanent residence is not available.

Benefits:

• National total target cash compensation of $161,000–$213,000 annually, including base salary and target bonus.
• Final compensation may vary based on experience, expertise, and geographic location.
• Stock options/equity opportunities.
• 401(k) plan with employer matching.
• Medical, dental, and FSA benefits.
• Long-term disability insurance.
• 12 paid holidays.
• Flexible paid time off.
• Mental health and family planning resources.
• Remote-first flexibility with the option to work from home, from the Boston office, or through a combination of both.
• High level of responsibility, autonomy, and ownership.
• Opportunities to work on challenging, high-impact data and product initiatives.
• Collaborative environment with opportunities for professional growth and career development.
• Employee meal program and additional office-based perks when working from the office.
• Opportunity to contribute to the transformation of workplace food and fulfillment experiences.

\n

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

 Why Apply Through Jobgether? 

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1