Senior Data Product Manager

Carrier•CAFLO: Carrier-Home Florida Remote Location, Remote City, FL, 33412 USA, FL

3d•$117,500 - $234,500

About The Position

The Data Product Manager is responsible for driving the successful delivery, adoption, and long‑term value of data products across data domains hosted on GCP. This includes areas such as parts and service, pricing, lead generation, external data integration, and broader commercial analytics. The role blends customer-facing leadership with strong data engineering and data product creation skills, ensuring that solutions are built on modern open lake house architecture and aligned with Carrier's business priorities. This leader partners with cross‑functional teams to translate business objectives into scalable, production‑ready data products that support enterprise transformation.

Requirements

Bachelor’s degree in computer science, Data Science, or Engineering AND 12 + years of experience in leading end-to-end product management, collaborating with cross-functional stakeholders, and delivering production-grade data analytics and data engineering solutions, including product roadmap execution and data model development.
OR Master’s degree in computer science, Data Science, or Engineering AND 10+ years leading end-to-end product management, collaborating with cross-functional stakeholders, and delivering production-grade data analytics and data engineering solutions, including product roadmap execution and data model development
5+ years of experience in Data Engineering on Google Cloud Platform (GCP), including the design, development, and implementation of open lakehouse architectures and medallion-based data products.
Must have unrestricted authorization to work in the USA. No visa sponsoring available.

Nice To Haves

Experience with cloud platforms AWS, Snowflake; familiarity with GCP AI/ML capability
Proficiency in SQL, Python, and modern ETL/ELT frameworks for building and supporting scalable data solutions.
Knowledge of data governance principles, including data quality, lineage, cataloging, metadata management, and access controls.
Experience integrating, modeling, and transforming data from enterprise systems, including ERP platforms such as SAP.
Understanding of commercial and operational analytics, including KPIs, funnel metrics, pricing structures, customer lifecycle analytics, and performance measurement.
Familiarity with machine learning workflows, AI-enabled data solutions, and MLOps practices.
Ability to translate business objectives into data product requirements and deliver solutions across multiple functional areas.
Experience leading cross-functional initiatives, engaging stakeholders, prioritizing multiple workstreams, and communicating effectively with both business and technical audiences.

Responsibilities

Serve as the primary delivery partner supporting GCP teams in shaping solution approaches, delivery plans, and customer adoption strategies across commercial and operational domains.
Lead discovery sessions with stakeholders in parts, pricing, sales operations, marketing, service, and analytics to define data product requirements and measurable outcomes.
Translate business needs into technical specifications, delivery roadmaps, and value‑focused product backlogs.
Build strong relationships with customer stakeholders to ensure alignment, transparency, and sustained value realization.
Own the end‑to‑end lifecycle of data products supporting use cases such as pricing optimization, parts availability insights, lead scoring, external data enrichment, customer segmentation, and commercial performance analytics.
Prioritize features and enhancements based on business value, feasibility, and customer impact.
Lead cross-functional delivery teams—including data engineers, analysts, platform engineers, and SMEs—through Agile execution.
Ensure data products follow medallion architecture principles (bronze/silver/gold) for quality, scalability, and reusability.
Oversee the design and development of data pipelines, transformations, and models using SQL, Python, and modern ETL/ELT frameworks.
Lead the implementation of open lake house architectures capable of supporting structured, semi‑structured, and unstructured data.
Ensure strong data quality, lineage, metadata management, and governance practices across all delivered products.
Support integration of diverse data sources including CRM, ERP/SAP, pricing systems, parts catalogs, marketing platforms, and external data providers.
Partner with commercial, operational, customer success, and engineering teams to ensure alignment across strategy, delivery, and adoption.
Communicate progress, risks, and outcomes to internal and external stakeholders.
Support pre-sales and solution‑shaping conversations when needed to validate delivery feasibility and architectural direction.