Manager, Data Engineering & Intelligence

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 Required Qualifications: 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 Preferred Qualifications: 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 Behavioral Traits for Success: 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 Working Environment: Typical office environment with climate control and sufficient lighting, ergonomic desk/chairs Hybrid work schedule Your Performance Will Be Measured On: 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 This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.