Manager, Data Engineering & Intelligence
Listed on 2026-02-12
-
IT/Tech
Data Engineer, Data Science Manager, Data Analyst, Data Security
Job Category: Information Technology
Requisition Number: MANAG
009631
Posted: December 9, 2025
Full-Time
Hybrid
LocationsShowing 1 location
415 S 18th St, St Louis, MO 63103, USA
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.
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
- 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
- Master’s degree in computer science, data science, or business administration
- 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
Your performance will be measured by your ability to achieve annual department objectives and corporate goals which include but are not limited to the following.
- Decision-making, judgment, and execution
- System reliability and scalability
- Team performance
- Performance metrics
- Accuracy
- Adherence to data policies
- Project delivery timelines
Compliance adherence - Data integrity
- Stakeholder Feedback
Equal Opportunity Employer
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