Staff Data Engineer

Xometry is looking for a Staff Data Engineer to join the 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 data systems are built and operated.

A defining piece of this role is owning the data architecture behind the DFM AI + IQE integration with a strategic partner. You will serve as the data engineering lead for the digital thread connecting the platform to partner ecosystems including Solid Edge, NX, Designcenter, and Teamcenter, building pipelines, data contracts, and observability to move quotes, parts, manufacturability signals, and pricing data in real time.

Responsibilities

• Lead the design and implementation of enterprise-scale data architecture and engineering solutions across multiple systems and domains
• Architect and build the data layer for embedded DFM AI + IQE integrations, including bidirectional pipelines and joint data models for parts, BOMs, quotes, and manufacturability signals
• Design low-latency signal paths delivering DFM and pricing feedback into designer environments
• Establish governance, lineage, and audit capabilities for partner-integrated data systems
• Architect and optimize reliable batch and streaming pipelines for complex, high-volume, event-driven data flows
• Own the full lifecycle of data engineering work from ingestion and transformation to delivery and observability
• Define and enforce best practices for data modeling, CI/CD, testing, code quality, contract testing, and schema evolution
• Solve complex cross-domain technical challenges aligned with business objectives
• Develop multi-quarter technical roadmaps and execution plans
• Collaborate with engineering, product, data science, business stakeholders, and partner engineering teams
• Mentor engineers through design and code reviews
• Evaluate and recommend tools, platforms, and architectural patterns

Qualifications

• Bachelor's degree in a STEM field (or equivalent experience)
• At least 5 years of experience in data engineering with ownership of complex, large-scale systems
• Deep expertise in Snowflake, including optimization and performance tuning
• Expert-level SQL and strong Python proficiency
• Experience with modern data tooling such as dbt, Airbyte, and Airflow
• Experience designing enterprise data architectures spanning multiple systems and partner boundaries
• Knowledge of batch and stream processing technologies (e.g., Kafka, Spark, Kinesis) and scalable data stores (e.g., Apache Iceberg)
• Experience building database-heavy services or APIs with focus on testability and maintainability
• Strong understanding of CI/CD, automated testing, contract testing, and schema evolution in data pipelines
• Strong knowledge of AWS and cloud-native infrastructure
• Enterprise integration experience with PLM, ERP, or large SaaS systems; Teamcenter experience is a strong plus
• Familiarity with data visualization tools such as Looker or Streamlit
• Experience with data governance, data quality frameworks, and observability tooling
• Exposure to lakehouse or data mesh architectures
• Experience with infrastructure as code (Terraform, CloudFormation)
• Experience with event-driven architectures, CDC pipelines, and low-latency operational data flows

Benefits

• Estimated base salary range: $180,000–$200,000 annually plus commission, depending on experience and location
• 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
• Employee assistance and wellbeing resources