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AD, Data Engineering

at Chewy

ChewyPlantation, FLOnsite

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Job Description: Our Opportunity Chewy’s AI & Data organization is seeking an Associate Director of Data Engineering to lead the teams that design, build, and govern the data foundation powering Chewy’s analytics, AI, and decision-making capabilities. As part of the Enterprise Data Systems (EDS) organization, you’ll oversee Data Engineering Managers and their teams—each owning a major domain such as Discover, Engage, Serve, and Participants. These teams build and govern end-to-end data products across Snowflake, dbt Cloud, Kafka, and BI platforms (Tableau, Sigma, Omni Analytics). You’ll shape the long-term data architecture, modernize pipelines through AI and automation, and ensure every domain operates from a consistent, reliable, and trusted foundation. You’ll lead technical direction, delivery excellence, and people growth while partnering closely with Product, Analytics, and AI platform leaders to execute Chewy’s enterprise data strategy. What You’ll Do Strategic Leadership & Vision Define and drive the multi-year technical vision for Chewy’s enterprise data platform covering ingestion, modeling, governance, and BI integration.Translate business and AI initiatives into a unified data engineering roadmap across domains (Discover, Engage, Serve, Participants).Establish and champion platform-wide standards for architecture, data modeling, testing, observability, and governance.Guide domain data teams to design interoperable, reusable, and AI-ready data products.Organizational Leadership & People Development Lead and mentor Data Engineering Managers and their teams of engineers.Partner with data owners across Chewy to set enterprise observability standards and champion best practices for data security and privacy, ensuring compliance.Develop a culture rooted in accountability, innovation, and continuous learning.Foster technical excellence, ensuring consistency in process and delivery across domains.Partner with Talent and HR to attract, grow, and retain top-tier data engineering and stewardship talent.Technical Direction & Modernization Oversee the evolution of Chewy’s Snowflake and dbt Cloud architecture, ensuring scale, performance, and cost efficiency.Champion real-time and event-driven architecture using Kafka and AWS-native tools.Guide adoption of new BI capabilities (Tableau, Sigma, Omni) with consistent governance and semantic layers.Drive standardization of reusable dbt packages, shared testing frameworks, and model documentation practices.AI & Automation Enablement Lead the integration of AI and automation into data engineering improving quality, reliability, and speed.Partner with the AI Platform team to expose governed data products for machine learning and generative AI use cases.Evaluate and implement AI-assisted tools for data lineage, documentation, anomaly detection, and self-healing pipelines.Promote a mindset where AI enhances the craft of data engineering rather than replacing it.Delivery Excellence & Governance Alignment Oversee roadmap execution and cross-domain dependencies, ensuring high-quality and predictable delivery.Align engineering and stewardship workstreams to deliver trusted, governed, and observable data.Partner with Product, Analytics, and Business leadership to ensure alignment on priorities and outcomes.Own KPIs for platform reliability, data quality, cost stewardship, and delivery throughput.Cross-Functional Partnership & Communication Act as a senior liaison between AI & Data, Product, and Business teams.Translate technical progress and strategy into clear narratives for executive stakeholders.Represent EDS in enterprise data councils, architecture forums, and AI leadership discussions.Drive alignment across Chewy’s ecosystem of data producers and consumers.What You’ll Need 10+ years of experience in data engineering or analytics platform leadership, including 4+ years managing managers.Deep technical expertise in Snowflake, dbt Cloud, and cloud-based data pipelines (Kafka, AWS).Strong understanding of data governance, lineage, and quality frameworks across warehouse

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