Manager, Data Engineering & Intelligence

StoreSt Louis, MO
11dHybrid

About The Position

The Manager, Data Engineering & Intelligence, leads a team responsible for building and maintaining scalable data pipelines, data warehouses, and analytical platforms that empower our retail business with actionable insights. The role is critical in enabling data-driven decision making through effective data infrastructure and intelligence solutions. The Manager, Data Engineering & Intelligence, combines strong technical expertise in data engineering with leadership skills and a business mindset to deliver high-quality, timely, and reliable data products across the organization.

Requirements

  • 7+ years of experience in data engineering or analytics, with at least 3 years in a leadership or management role
  • Bachelor’s degree in computer science, data science, engineering, or related field
  • Expert use of SQL/Python
  • Skilled in Data Engineering tools (Airflow, dbt, Spark, Kafka)
  • Proficiency with BI Tools (Power BI)
  • Skilled in Cloud Data Platforms (AWS, Azure, GCP)
  • Proficient knowledge of SOC-1, GDPR, and CCPA compliance

Nice To Haves

  • Master’s degree in computer science, data science, or business administration
  • AWS Certified Data Engineer
  • Microsoft Certified: Azure Data Engineer Associate, or Google Professional Data Engineer
  • Strong leadership, collaboration, and communication skills
  • Proven success in managing cross-functional teams
  • Retail or consumer goods industry experience
  • Experience with Fabric, Snowflake, Databricks, or similar modern data platforms
  • Familiarity with machine learning pipelines and analytics enablement
  • Strong understanding of metadata management and data cataloging practices
  • Demonstrated ability to innovate and automate within data engineering frameworks
  • An analytical, inquiring, and critical mind that solves complex problems with ingenuity
  • Driven to produce high-quality work within established standards of quality and accuracy
  • Drive, determination, and self-disciplined approach to achieving results
  • Communication style is concise, factual, and professional
  • Comfortable making decisions within area of expertise
  • Tests new ideas and concepts before releasing
  • Earns trust by consistently achieving high-quality standards in a timely manner
  • Able to manage multiple priorities

Responsibilities

  • Lead and mentor a team of data engineers and analysts
  • Design and maintain scalable, high-performance data pipelines and warehouses
  • Ensure data quality, integrity, security, and compliance throughout the data lifecycle
  • Collaborate with business and analytics teams to translate requirements to solutions
  • Evaluate and recommend new data technologies, platforms, and methodologies to improve efficiency
  • Champion data quality, governance, and compliance standards
  • Communicate progress, challenges, and insights to senior leadership and partners
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