Manager, Data Products

Manager, Data Products page is loaded## Manager, Data Productslocations: SSC Irving TXtime type:
Full time posted on:
Posted Todayjob requisition : R26 5750
* 7-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants and fuel through cutting edge innovation - working hard to be the customer's first choice. 7-Eleven empowers our employees to "activate awesome" and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead and make a difference, come join our team and help shape the future of convenience.*##

About This Opportunity##Manage the team that turns enterprise data into trusted products people can use to make decisions, run the business, and serve customers and stores. Own data products from discovery through retirement, including the roadmap, requirements, delivery, adoption, quality, support, and value tracking. Work in the 7-Eleven Enterprise Data Platform environment with teams that build and support Databricks-based data pipelines, medallion architecture, reusable datasets, master and reference data, governed metrics, semantic models, Power BI reporting, self-service analytics, and AI-assisted data experiences.

Use tools such as Databricks, Unity Catalog, Alation, Monte Carlo, Power BI, Dataiku, and approved AI tools to help make data products discoverable, governed, secure, observable, reliable, and useful. Partner closely with business owners, data engineering, architecture, platform, analytics, data science, privacy, security, and governance teams to define what each product should do, how it should be used, how it will be supported, and how value will be measured.

Forecast staffing and costs, manage team capacity, and guide the team in using automation and AI to reduce manual effort, improve self-service, and increase trust in enterprise data.#

KEY RESPONSIBILITIES ## 1. Product Lifecycle
· Own the full lifecycle for internal and external data products, from discovery and design through launch, support, improvement, and retirement.
· Work with business users to understand the problem, define the intended outcome, identify the right data, and agree on how success will be measured.
· Set and maintain product vision, roadmaps, priorities, requirements, acceptance criteria, release plans, and product documentation.
· Make sure each data product has a clear owner, purpose, user group, support model, quality expectations, metadata, lineage, refresh timing, known limits, and measurable business value.
· Manage data products that may include enterprise datasets, data marts, master and reference data, governed metrics, reporting datasets, semantic models, APIs, and data used by AI/ML, analytics, and operational systems.## 2. Product Delivery
· Translate business needs into clear features, user stories, data rules, source-to-target needs, acceptance criteria, and delivery plans that engineering and analytics teams can execute.
· Manage and prioritize the backlog based on business value, urgency, data availability, technical complexity, risk, platform cost, support impact, and team capacity.
· Partner with data engineers, analysts, data scientists, architects, privacy, security, platform, and data governance teams to balance speed, quality, controls, cost, and long-term maintainability.
· Work with engineering and architecture teams on practical product design choices, including batch or streaming patterns, Databricks medallion layers, reusable components, data contracts, semantic models, and downstream consumption patterns.
· Identify dependencies, risks, data gaps, scope changes, access needs, platform constraints, and key decisions early so delivery stays…