Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and is on track to double our revenue in the next 18 months. To meet and exceed this target, Stord is strategically scaling teams across the entire company, and seeking energetic experts to help us achieve our mission.
By combining comprehensive commerce-enablement technology with high-volume fulfillment services, Stord provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale.
With Stord, brands can increase cart conversion, improve unit economics, and drive sustained customer loyalty. Stord's end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order.
Hundreds of leading DTC and B2B companies like AG1, True Classic, Native, Seed Health, quip, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures.
The Senior Director of Data Engineering is focused on architecting and scaling our next-generation data infrastructure that powers AI-driven logistics and real-time customer experiences. This role combines strategic vision with hands-on technical leadership to transform how we leverage data as a competitive advantage. The Senior Director of Data Engineering will lead our existing team of engineers and analysts while scaling the team in the coming year, partnering closely with AI Products, Engineering, and Operations teams. This position can be remote US or hybrid based in Atlanta, with occasional travel for team collaboration and strategic planning sessions.
Lead Major Data Platform Transformation: Architect and execute our multi-million dollar modernization from legacy infrastructure to cloud-native, AI-ready data systems supporting $10B+ in commerce annually
Build AI-First Data Infrastructure: Design and implement real-time streaming architectures, feature stores, and MLOps pipelines that enable demand forecasting, intelligent routing, and autonomous warehouse operations
Scale High-Performance Teams: Transform and grow our data engineering organization from EDW-focused to full-stack capabilities, building career development frameworks and establishing engineering excellence practices
Drive Direct Business Impact: Partner with cross-functional teams to deliver embedded analytics, predictive models, and data products that increase customer retention, optimize operations, and enable revenue growth
Architect Competitive Advantages: Create data systems and capabilities that differentiate Stord in the market, enabling real-time insights, proactive customer communication, and AI-powered supply chain intelligence
Bachelor's degree in Computer Science, Engineering, or related technical field
10+ years of data engineering leadership experience with proven track record of scaling teams and delivering complex technical transformations at high-growth companies
Expert-level experience with modern data stack technologies including BigQuery, DBT, streaming platforms (Kafka/Pulsar), and cloud-native architectures (GCP preferred)
Hands-on experience building both traditional data warehouses and real-time ML infrastructure including feature stores, model serving, and MLOps pipelines
Demonstrated success in team leadership, technical mentorship, and establishing data governance frameworks at scale
Strong business acumen with ability to translate technical strategy into measurable business outcomes and communicate effectively with C-level executives
Experience with logistics, commerce, supply chain, or high-volume operational data domains
Track record implementing cutting-edge AI/ML systems in production environments with strict SLA requirements
Previous experience at companies processing billions in transactions or managing complex multi-tenant data architectures
Advanced degree in Computer Science, Data Science, or related field