Staff Data Engineer

Staff Data Engineer role on Xometry’s Data Platform team, focused on data architecture and scalable batch and streaming pipelines/platforms with broad technical impact.

Responsibilities

• Lead with technical depth by designing and driving enterprise-scale data architecture and engineering solutions across multiple systems and domains
• Own the partner integration data plane for the embedded DFM AI + IQE integration with partner Teamcenter and Designcenter
• Build bidirectional pipelines and a joint data model covering parts, BOMs, quotes, and manufacturability signals
• Deliver a low-latency signal path that sends DFM and pricing feedback back into the designer’s environment
• Define governance, lineage, and audit posture for a public-marketplace partner integration
• Build for scale by architecting and optimizing reliable batch and streaming pipelines, data models, and platforms for high-volume data and real-time/event-driven partner flows
• Own the full lifecycle from data acquisition and transformation through delivery, observability, and ongoing performance
• Set the standard for best practices in data modeling, CI/CD, testing, and code quality, including contract-testing and schema evolution when data crosses a partner boundary
• Solve ambiguous problems across cross-domain requirements, balancing business and technical objectives
• Develop multi-quarter roadmaps by translating strategic priorities into technical plans with independent ownership of methods and timelines
• Collaborate broadly with engineers, product managers, data scientists, business stakeholders, and partner engineering teams to deliver robust solutions
• Mentor and elevate engineers through design reviews, code reviews, and technical mentorship
• Evaluate and adopt by staying current with the data engineering ecosystem and recommending tools, platforms, and architectural patterns

Requirements

• Bachelor’s degree in a STEM field (or equivalent experience) plus at least 5 years in a data engineering related role with demonstrated ownership of complex, large-scale data systems
• Deep expertise with cloud data warehouses, with Snowflake strongly preferred, including optimization, best practices, and performance tuning
• Expert-level SQL and strong Python proficiency; ability to pick up additional languages as needed
• Hands-on experience building and optimizing pipelines, architectures, and datasets using modern tooling such as dbt, Airbyte, Airflow (or similar)
• Demonstrated experience planning and implementing enterprise data architecture across multiple systems and domains, including cross-organizational or partner boundaries
• Working knowledge of queueing, batch and stream processing (Kafka, Spark, Kinesis) and highly scalable data stores such as Apache Iceberg
• Experience writing database-heavy services or APIs and designing for testability and maintainability
• Deep understanding of CI/CD with automated testing, contract testing, and schema evolution practices 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 across the organization, including with external partner engineering teams
• Enterprise/partner integration experience integrating with PLM, ERP, or large enterprise SaaS; partner Teamcenter experience (data model, BMIDE, Active Workspace APIs, AWC integrations) or comparable PLM exposure is a strong plus
• Familiarity with data visualization tools such as Looker and Streamlit
• Experience with data governance, data quality frameworks, and observability tooling, especially when data flows across partner or tenant boundaries
• Exposure to modern lakehouse or data mesh architectural patterns
• Experience with infrastructure as code (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

Technologies

• Snowflake
• SQL
• Python
• dbt
• Airbyte
• Airflow
• Kafka
• Spark
• Kinesis
• Apache Iceberg
• AWS
• Looker
• Streamlit
• Terraform
• CloudFormation
• Teamcenter
• Designcenter
• Solid Edge
• NX
• BMIDE
• Active Workspace APIs
• AWS integrations
• CDC pipelines
• Iceberg

Benefits

• 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 and other wellbeing resources

Location: Denver, CO (hybrid)

Compensation: USD 180,000 - 200,000 per yearly