Define and communicate the vision, strategy, and roadmap for Distribution & Marketing data products; align outcomes, KPIs, and success measures with stakeholders.

Translate business needs into epics and user stories with clear acceptance criteria; maintain and prioritize the backlog.

Lead one or more engineering squads through discovery, backlog grooming, and delivery with a strong definition of done in a matrixed environment.

Partner across stakeholders in business, data engineering, architecture, security, reporting and analytics to drive alignment, build AI ready data products for scale; evaluate build vs. buy and guide POCs.

Embed data governance, security, and compliance controls into product design and delivery.

Communicate status, risks, and trade-offs to business and technical stakeholders in plain language; make timely decisions to keep delivery on track.

Monitor product KPIs and operational health; reduce incidents and improve development cycle time through continuous improvement.

Manages moderately complex projects and recommends and implements new or enhanced data products to better meet stakeholder or customer needs by leading the development of project backlogs and plans, including milestones and dates, identification of parties and processes impacted by a data solution.

Ability to grasp new technologies needed to progress initiatives, while demonstrating an understanding of the use of data in solving a business use case.

Can create roadmaps for product delivery, innovate, and create new product ideas.

Able to prioritize efforts based on customer value.

Can communicate to a senior audience how technical designs meet business needs, and shows a command of industry trends and business processes.

Able to break down data issues and resolve them, by prototyping data solutions to meet the needs of both the organization and business customers.

Ability to think through proof-of-concept solutions and how they will be maintained, and can help assess whether proof-of-concepts are viable and scalable by partnering with IT.

The final job grade level will be determined based on the successful candidate's relevant experience and qualifications. 5+ years (ideally 5-7+) in data product management, analytics, data engineering, or a related role, including hands-on experience with data warehousing, ELT/ETL, and software design principles.

Demonstrated product ownership: roadmap development, prioritization, acceptance criteria, stakeholder management, and Agile delivery.

Experience: influencing and aligning stakeholders in large, matrixed organizations; able to communicate recommendations to senior leaders and simplify technical topics for business and engineering audiences.

Strong problem-solving skills: decompose ambiguous problems, form hypotheses, run tests, and make data-driven decisions.

Proficiency in SQL and familiarity with data marts, data models and pipelines; Snowflake experience strongly preferred. BI tools (e.g., Power BI, SAS); Python or other scripting experience is a plus.

Knowledge of cloud data platforms and data governance, privacy, and security best practices.

Domain experience in Distribution & Marketing preferred.

Strong written and oral communication skills required

Experience: in communicating recommendations to senior business leaders preferred BA/BS, or relevant work experience, in Computer Science or related field preferred MBA or advanced degree in Mathematics, Computer Science, Engineering, Economics, or other quantitative discipline strongly preferred 5-7+ years of experience working in coding and data solutions design principles, particularly in open source tools and technology