Senior Manager, Data Engineering

## Senior Manager, Data Engineering Apply:
SSC Irving TX:
Full time:
Posted Today:
R26 _5743
* 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.
* We are looking for an experienced Engineering Manager to lead the Data Engineering team.  At 7-Eleven, Enterprise Data powers decisions for everyone from store managers to the C-suite. The
** Data Engineering
** team is the backbone of that ecosystem — designing and operating the
** batch and streaming ELT pipelines, lakehouse models, and master data systems
** that feed hundreds of enterprise reports, daily decision reports, and downstream AI applications You will lead a multi-pod team responsible for ingestion, transformation, modeling, and run-engineering across nine business domains.  
** Responsibilities
* * As the Senior Manager of the Data Engineering team, you will:
· Manage day-to-day delivery across multiple Data Engineering pods (~25–30 engineers across onshore/offshore teams), building and operating ingestion, ELT, streaming, and lakehouse pipelines across business domains such as Digital, Merchandising, Operations, Finance, Customer & Marketing, Fuel, and Supply Chain.
· Set the technical vision for Data Engineering—driving enterprise master data programs, historical/backfill strategy, intake maturity, change-control automation, and modernization of legacy ETL into a lakehouse architecture.
· Partner with Data Architects to translate conceptual and logical models into physical implementations using Delta/Lakehouse platforms—applying medallion patterns, dimensional modeling, and consistent intake contracts.
· Partner with Data Platform, Governance, and Quality teams to ensure every pipeline includes observability, data quality rules, lineage, and privacy classifications by design.
· Own delivery of legacy reporting and analytics modernization initiatives—refactoring OLAP-style models into dimensional models, repointing reports to modern BI platforms, and decommissioning legacy systems.
· Run the Data Engineering function as a product organization—managing backlog, business cases, enterprise prioritization, and adoption/value tracking for delivered data products.
· Mentor engineers, technical leads, and managers, and coach offshore engineering teams on modernization, code quality, and developer experience standards.
· Partner with Platform teams on CI/CD, AI-assisted SDLC, and cost attribution to ensure data workloads are observable, attributable, and cost-efficient.
· Own incident response and SLA adherence for production pipelines supporting critical business and AI-driven applications.  
** Qualifications*
* · 8+ years of professional experience in Software Engineering, Data Engineering, or Analytics Engineering.
· 5+ years designing and operating large-scale data pipelines (batch and streaming ELT/ETL) in lakehouse or data warehouse environments.
· 5+ years working with distributed compute frameworks (Spark/Databricks strongly preferred; Delta Lake, Unity Catalog, Workflows, DLT a plus).
· 5+ years managing engineering teams, ideally across multiple pods with hybrid onshore/offshore delivery models.
· Strong knowledge of data modeling (dimensional/Kimball, data vault, medallion patterns) and experience translating conceptual models into physical implementations.
· Strong knowledge of master data management concepts and…