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