Senior Manager of Data Engineering – Enterprise Data Platform

4 weeks ago

Irving, United States 7-Eleven Full time

Overview

7-Eleven is looking for a Senior Manager of Data Engineering to join the Enterprise Data Platform Team. This role would report into the Senior Director of Data, AI/ML, and R&D.


At 7-Eleven, we’re creating the next generation of convenience, and we know that the best way to do that is with great people. If you get excited about solving data problems at peta-byte scale, keep reading


About the job:

As a Senior Manager of Data Engineering, you will lead a team of data engineers working on our core data infrastructure and data platform initiatives. This role requires a highly skilled and hands-on data professional with expertise in Databricks, Azure, AWS, Kafka, and both SQL and noSQL databases. You will own and drive the data strategy and roadmap for the enterprise platform, with an alignment to key business initiatives. The ideal candidate will have deep technical expertise, strong communication skills, and a focus on growing and retaining technical talent.


Key Responsibilities:

Leadership Responsibilities

  • Lead and mentor a team of data engineers
  • Recruit, retain, and grow talent with a focus on technical excellence
  • Oversee the design, implementation, and maintenance of scalable data pipelines in a multi-cloud environment, including integrations with a variety of data sources (including structured, semi-structured, and unstructured data)
  • Own the strategy and Roadmap for Data Engineering in the context of the company’s Data and AI strategy
  • Collaborate with counterparts in Architecture, Machine Learning, and Data Governance to deliver data platform initiatives
  • Drive a high bar for technical excellence across the engineering team
  • Communicate with non-technical business stakeholders, ensuring understanding and alignment on key data initiatives for the business
  • Manage project timelines, resources, and budgets to ensure the timely delivery of data engineering projects, including those related to retail analytics and reporting.


Technical Responsibilities

  • Oversee the design, implementation, and maintenance of scalable data pipelines in a hybrid cloud environment.
  • Manage the integration of various data sources, including structured, semi-structured, and unstructured data.
  • Ensure data engineering standards align with industry best practices for data governance, data quality, and data security.
  • Implement data processing frameworks, including batch and real-time processing, with a focus on retail-specific data such as sales, inventory, and customer behavior.
  • Collaborate with business stakeholders to understand data needs specific to retail operations and translate them into actionable data engineering solutions.
  • Monitor and optimize the performance of data pipelines, ensuring they meet SLAs for data availability and quality, especially for retail-critical operations.
  • Evaluate and recommend new data technologies and tools to improve data engineering processes and outcomes, with a focus on retail domain requirements.



Basic Qualifications:

  • 8+ years of experience working in an engineering role, with a focus on large-scale data environments
  • 5+ years of experience in a leadership or management role, guiding teams of engineers.
  • 2+ years of experience as a manager of managers

Strong experience with Azure Cloud, AWS, and on-premises infrastructures.

  • Expertise in designing and implementing scalable data pipelines using tools such as Apache Spark, Databricks, Kafka, and others.
  • Solid understanding of data warehousing, data lakes, and modern data architectures (e.g., Data Mesh, Medallion Architecture).
  • Experience with data processing frameworks, both batch and real-time (e.g., Spark, Flink, Storm).
  • Proficiency in programming languages commonly used in data engineering, such as Python, Scala, or Java.
  • Strong understanding of database technologies, including SQL and NoSQL databases.
  • Experience with CI/CD pipelines and DevOps practices for data engineering.
  • Excellent problem-solving and analytical skills.
  • Strong communication skills to articulate complex data requirements to both technical and non-technical stakeholders.
  • Bachelor’s Degree or higher in Computer Science/Engineering/Math, or relevant experience


Extra Credit:

  • Experience working in the retail industry, with knowledge of retail data structures, sales forecasting, inventory management, and customer analytics.
  • Previous experience partnering with Machine Learning platform teams
  • Knowledge of Agile methodologies and experience working in Agile teams.
  • Experience with data governance and data quality initiatives.
  • Familiarity with design thinking principles.
  • Relevant certifications in data engineering or cloud technologies (e.g., Azure Data Engineer, AWS Certified Data Analytics).
  • Experience with retail-specific technologies and tools, such as POS systems, ERP systems, and customer loyalty programs.

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