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.

Stord runs on data - every pallet moved, every order fulfilled, and every model our AI team ships depends on data that's fast, clean, and easy to find. As our Senior Data Engineer, you'll own that ecosystem: designing, building, and maintaining the pipelines and infrastructure that turn raw operational data into something the whole business can act on. You'll work closely with data scientists, analysts, and software engineers in a cloud-native environment, building for where Stord is headed, not just where it's been.

We move over $10 billion in commerce a year across fulfillment, warehousing, and supply chain software. You'll build the infrastructure that turns that volume into reliable, governed, ML-ready data - including the foundations our agentic AI tooling runs on.

What You'll Own:

• Design and build scalable data pipelines using GCP services like Cloud Dataflow, Cloud Pub/Sub, Data Stream, Spark, and Cloud Composer, ingesting, processing, and storing large datasets from multiple sources

• Develop, test, and maintain data models, schemas, and ETL (Extract, Transform, Load) processes using BigQuery, Cloud SQL, Spark, and Data Studio

• Partner with stakeholders to understand business requirements and translate them into data infrastructure that actually solves the problem

• Optimize data pipelines for performance, scalability, and cost efficiency, using GCP-native tools such as Dataproc and Bigtable

• Ensure data quality, integrity, and security by building validation processes and enforcing data governance, access control, and security best practices

• Automate workflows using Cloud Composer so pipelines run reliably and on schedule, not by accident

• Own pipeline and data infrastructure reliability end-to-end — monitoring, alerting, troubleshooting, and root cause analysis — partnering with SRE and Infrastructure on shared GCP resources (compute, storage, network) rather than handing reliability off to someone else

• Prepare, model, and expose data for ML and agentic AI use cases, including the governed data pipelines Stord's AI tooling queries in production

• Mentor the broader data team as a senior technical voice on pipeline design and data infrastructure standards

• Stay ahead of GCP's roadmap and emerging best practices, and put what you learn back into the platform

What You'll Bring:

• 5+ years of data engineering experience, including at least three years in a cloud environment (preferably GCP)

• Expertise across GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, Cloud Functions, and Cloud SQL

• Strong SQL, with real experience writing complex queries for data extraction and analysis

• Hands-on ETL development and workflow orchestration using tools like Apache Airflow

• Proficiency in Python and/or Spark for data processing and pipeline development

• Experience with streaming data pipelines (Pub/Sub, Dataflow, or similar) as well as batch processing

• A solid grasp of data warehousing concepts, large datasets, and query optimization

• Working knowledge of data governance, security, and compliance in a cloud environment

• Understanding of ML concepts and data preparation for ML applications, with interest in agentic AI tooling a must

• Strong analytical, problem-solving, and troubleshooting instincts, with real attention to detail

• Clear, confident communication and the ability to collaborate across teams

Nice to Haves:

• Bachelor's degree in computer science or a comparable field, or equivalent experience

• GCP certification (Professional Data Engineer or Cloud Architect)

• Experience with ML infrastructure on GCP, such as AI Platform and TensorFlow

• Familiarity with DevOps/MLOps practices — CI/CD, infrastructure as code (Terraform), and containerization (Kubernetes, Docker) on GCP

• Experience with other data processing frameworks, such as Apache Spark

• A background in logistics, supply chain, 3PL, or warehouse/fulfillment technology

• Experience working on a distributed team