Staff Data Engineer

Xometry is looking for a Staff Data Engineer to join our Data Platform team. This is a senior individual contributor role with broad technical scope and high organizational impact. You will own data architecture decisions, lead the design of scalable pipelines and platforms, and set the engineering bar for how we build and operate our data systems. You will partner closely with engineering, product, analytics, and machine learning teams to ensure our data infrastructure enables the business to move fast and make high-quality decisions. Everything you build will matter. A defining piece of this role is owning the data architecture behind one of Xometry's highest-leverage strategic initiatives: the DFM AI + IQE integration with our partner. You will be the data engineering lead for the digital thread that connects Xometry's platform to the partner ecosystem — Solid Edge, NX, Designcenter, and Teamcenter — building the pipelines, contracts, and observability that move quotes, parts, manufacturability signals, and pricing between the two systems in real time. The data plane you design is what makes the "science fiction speed" digital thread from ideation to delivery actually work.

How You’ll Contribute:

What You'll Bring to Xometry:

• Bachelor's degree in a STEM field (or equivalent experience) plus at least 5 years of experience in a data engineering related role, with demonstrated ownership of complex, large-scale data systems
• Deep expertise with cloud data warehouses – Snowflake strongly preferred – including optimization, best practices, and performance tuning
• Expert-level SQL and strong Python proficiency; comfort picking up additional languages as needed
• Hands-on experience building and optimizing data pipelines, architectures, and data sets using modern tooling (dbt, Airbyte, Airflow, or similar)
• Demonstrated experience planning and implementing enterprise data architecture across multiple systems and domains, including integrations that cross organizational or partner boundaries
• Working knowledge of queueing, batch and stream processing (e.g., Kafka, Spark, Kinesis), and highly scalable data stores (e.g., Apache Iceberg)
• Experience writing database-heavy services or APIs and designing for testability and maintainability
• Deep understanding of CI/CD principles and demonstrated experience with automated testing, contract testing, and schema-evolution discipline in data pipelines
• Strong grasp of the AWS data ecosystem and cloud-native infrastructure
• Ability to operate independently on new and ambiguous assignments, determine methods and procedures, and communicate effectively at all levels of the organization — including with external partner engineering teams
• Enterprise / partner integration experience – Prior work integrating with PLM, ERP, or large enterprise SaaS systems; partner Teamcenter experience (data model, BMIDE, Active Workspace APIs, AWC integrations) or comparable PLM exposure is a strong plus
• Familiarity with data visualization tools (e.g., Looker, Streamlit)
• Experience with data governance, data quality frameworks, and observability tooling — especially in contexts where data flows across partner or tenant boundaries
• Exposure to modern lakehouse or data mesh architectural patterns
• Experience with infrastructure as code (IaC) frameworks (e.g., Terraform, CloudFormation)
• Experience with event-driven architecture, CDC pipelines, and low-latency operational data flows that feed back into a customer-facing UI
• Experience in manufacturing, supply chain, or marketplace environments is a plus — but curiosity and drive matter more

We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

#LI-Hybrid