<p>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.</p> <p>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.</p> <p>Responsibilities:</p> <ul> <li>Lead and mentor a team of data engineers and analysts </li><li>Design and maintain scalable, high-performance data pipelines and warehouses </li><li>Ensure data quality, integrity, security, and compliance throughout the data lifecycle </li><li>Collaborate with business and analytics teams to translate requirements to solutions </li><li>Evaluate and recommend new data technologies, platforms, and methodologies to improve efficiency </li><li>Champion data quality, governance, and compliance standards </li><li>Communicate progress, challenges, and insights to senior leadership and partners </li></ul> <p>Required Qualifications:</p> <ul> <li>7+ years of experience in data engineering or analytics, with at least 3 years in a leadership or management role </li><li>Bachelor's degree in computer science, data science, engineering, or related field </li><li>Expert use of SQL/Python </li><li>Skilled in Data Engineering tools (Airflow, dbt, Spark, Kafka) </li><li>Proficiency with BI Tools (Power BI) </li><li>Skilled in Cloud Data Platforms (AWS, Azure, GCP) </li><li>Proficient knowledge of SOC-1, GDPR, and CCPA compliance </li></ul> <p>Preferred Qualifications:</p> <ul> <li>Master's degree in computer science, data science, or business administration </li><li>AWS Certified Data Engineer </li><li>Microsoft Certified: Azure Data Engineer Associate, or Google Professional Data Engineer </li><li>Strong leadership, collaboration, and communication skills </li><li>Proven success in managing cross-functional teams </li><li>Retail or consumer goods industry experience </li><li>Experience with Fabric, Snowflake, Databricks, or similar modern data platforms </li><li>Familiarity with machine learning pipelines and analytics enablement </li><li>Strong understanding of metadata management and data cataloging practices </li><li>Demonstrated ability to innovate and automate within data engineering frameworks </li></ul> <p>Behavioral Traits for Success:</p> <ul> <li>An analytical, inquiring, and critical mind that solves complex problems with ingenuity </li><li>Driven to produce high-quality work within established standards of quality and accuracy </li><li>Drive, determination, and self-disciplined approach to achieving results </li><li>Communication style is concise, factual, and professional </li><li>Comfortable making decisions within area of expertise </li><li>Tests new ideas and concepts before releasing </li><li>Earns trust by consistently achieving high-quality standards in a timely manner </li><li>Able to manage multiple priorities </li></ul> <p>Working Environment:</p> <ul> <li>Typical office environment with climate control and sufficient lighting, ergonomic desk/chairs </li><li>Hybrid work schedule </li></ul> <p>Your Performance Will Be Measured On:</p> <p>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.</p> <ul> <li>Decision-making, judgment, and execution </li><li>System reliability and scalability </li><li>Team performance </li><li>Performance metrics </li><li>Accuracy </li><li>Adherence to data policies </li><li>Project delivery timelines </li><li>Compliance adherence </li><li>Data integrity </li><li>Stakeholder Feedback </li></ul>