# Senior Data Product Manager, Delivery Transformation

**Company:** [ezCater](https://hotfix.jobs/companies/ezcater)
**Location:** Remote
**Role:** Product Management
**Experience:** 7+ years
**Skills:** SQL, data product management, Data Modeling, Data Warehousing, data lakehouse, ELT, semantic layers, metrics architecture, Data Governance, Data Quality, data observability, Machine Learning, Data Science, data lineage, Access Control
**Posted:** 2026-08-03

> Owns the fulfillment data domain as a product, defining canonical models, metrics architecture, governed data products, and signals for analytics and machine-learning decisioning. Requires 7+ years in data or analytics environments and strong experience with data product ownership, SQL, governance, and cross-functional delivery.

## Job Description

## Responsibilities

- Own the fulfillment data asset as a product, including its vision, strategy, adoption, and return.
- Define and evolve the canonical fulfillment lifecycle model covering events, entities, relationships, and happy, alternate, and exception paths.
- Define the metrics architecture across operational, capability, geographic, coverage, and performance views.
- Build governed, trusted analytics and platform data products for self-service, direct query, telemetry, and model signals.
- Provide reliable data foundations, signals, telemetry, and feedback loops for intelligent routing, pickup-time prediction, risk scoring, and service-level decisions.
- Decompose work into estimable data-product units and drive dated commitments, milestones, dependency tracking, and trade-offs.
- Own data reliability, freshness, accuracy, service levels, observability, incident resolution, and cost.
- Drive adoption, documentation, enablement, business validation, and measurable impact.
- Connect the fulfillment domain to the Enterprise Data Hub, governed semantic layer, cataloging, and enterprise data governance.
- Partner with engineering, architecture, delivery operations, analytics, data platform, data architecture, and business stakeholders.

## Requirements

- 7+ years working in or directly with data engineering, data platform, analytics, or data-product teams, ideally in complex, multi-system environments.
- 5+ years owning data or analytics products, with direct data product management experience preferred.
- End-to-end data product ownership from discovery and requirements through launch, adoption, and measurable business impact.
- Experience defining data domains from the ground up, including canonical or domain modeling, event and entity design, and metrics or KPI architecture.
- Familiarity with modern cloud data warehouses and lakehouse architectures, ELT and transformation patterns, modeling frameworks, semantic layers, and metrics layers.
- Strong SQL and ability to explore data and metadata, including usage, quality, lineage, and cost.
- Experience partnering with data science and machine learning teams on reliable data access, signals and features, performance, and monitoring.
- Working knowledge of data governance, classification, access control, data quality, and observability.
- Ability to build and execute multi-quarter, multi-team plans and communicate trade-offs.
- Strong delivery discipline, communication, and stakeholder management across technical and business audiences.
- Ability to travel up to 5 days per quarter for team gatherings and other events, when applicable.

## Nice to Have

- Experience in logistics, last-mile delivery, marketplace, food, or fulfillment domains.
- Familiarity with dispatch, routing, tracking, and driver and partner dynamics.
- Experience building data foundations for routing, risk scoring, forecasting, or recommendation systems.
- Familiarity with AI-powered data-platform patterns, semantic layers, retrieval and search, and conversational analytics.
- Experience building on or migrating onto a governed enterprise data platform and semantic layer.

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