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Senior Manager, Enterprise Data Platform7-Eleven • Irving, Texas, United States
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Senior Manager, Enterprise Data Platform

7-Eleven
  • US
    Irving, Texas, United States
  • US
    Irving, Texas, United States
Postuler Maintenant

À propos

Engineering Manager

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.

7-Eleven is looking for an experienced Engineering Manager to lead the Enterprise Data Platform team.

At 7-Eleven, Enterprise Data is the aggregator of all large-scale datasets across the organization. We operate the Enterprise Data Lakehouse and Analytics Platform on Azure + Databricks (Unity Catalog), producing reports, metrics, and AI/ML-driven insights for users ranging from C-level executives to store managers. The Enterprise Data Platform team owns the infrastructure, governance plumbing, and automation that lets our Data Engineers, Analysts, and Data Scientists move at full speed and ensures every dollar of our annual platform spend is observable, attributable, and tied back to a data-product owner.

Responsibilities
  • Manage day-to-day delivery across multiple Platform Engineering pods building and maintaining the cloud infrastructure and automated processes that power Data Engineering, Analytics, and Machine Learning verticals.
  • Set the multi-year vision for the Data Platform identifying gaps in the stack, defining a roadmap (Workspace migration, Serverless adoption, CI/CD, AI-assisted SDLC, cost attribution), and positioning EDP to deliver data-product-driven applications at enterprise scale.
  • Partner with Data Architects to design scalable, maintainable, cost-efficient pipelines and shared services meeting best practices for cloud infrastructure, lakehouse modeling, and analytics engineering.
  • Partner with Data Governance, Privacy, and Compliance leaders to scale the rollout of governed data products including auditing, lineage, discoverability (Alation), data quality, and privacy controls (e.g., consumer rights handling).
  • Drive cost attribution and chargeback extend tagging coverage from workspace-level to table/compute/job-level, accelerate Databricks Serverless adoption, and give product owners visibility into their true unit economics.
  • Lead change management for new data initiatives and tools running presentations, workshops, office hours, and training material to drive adoption across 7-Eleven.
  • Mentor engineers, technical leads, and engineering managers in their personal growth and careers including cross-coaching with our GSC counterparts.
  • Own the Site Reliability and Support function for the Enterprise Data Platform incident management, automated observability, ticketing, ITSM, and 247 on-call.
Qualifications
  • All qualifications are representative of the experience level we are targeting you do not need to meet every bullet.
  • 8+ years professional experience as a Software Engineer, Data Engineer, DevOps Engineer, or similar.
  • 5+ years in DevOps, Platform Engineering, or Cloud Infrastructure.
  • 3+ years in Data Engineering, Data Analytics, or AI/ML.
  • 3+ years managing engineering teams preferably multiple teams concurrently, including hybrid onshore/offshore (SSC + GSC) models.
  • High proficiency with AI productivity and AI driven automation and agentic workflows
  • Experience owning Incident Response, on-call rotations, knowledge bases, and ITSM tooling.
  • Deep technical knowledge of cloud infrastructure Azure preferred; AWS or GCP acceptable.
  • Deep knowledge of application and infrastructure observability logging, monitoring, alerting, and automated incident tracking.
  • Strong knowledge of Data Engineering and Analytics fundamentals data modeling, ELT/ETL pipeline design, distributed compute (Spark/Databricks).
  • Strong knowledge of deploying AI/ML in production feature engineering, model selection, deployment, and ML-Ops.
  • Strong communication and storytelling skills able to translate engineering progress into executive narratives and bubble information up to senior leaders.
  • Strong project- and time-management skills comfortable producing PM artifacts (roadmaps, Gantt charts, process diagrams, status reporting) for active engineering programs.
  • Irving, Texas, United States

Compétences linguistiques

  • English
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