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. You will build the pipelines, contracts, and observability that move quotes, parts, manufacturability signals, and pricing between systems in real time.

Responsibilities

• Lead with technical depth – Design and drive the implementation of enterprise-scale data architecture and engineering solutions spanning multiple systems and domains.
• Own the partner integration data plane – Architect and build the data layer of the embedded DFM AI + IQE integration with Teamcenter and Designcenter, including bidirectional pipelines, joint data models, low-latency feedback paths, governance, lineage, and audit controls.
• Build for scale – Architect and optimize reliable batch and streaming data pipelines, data models, and platforms handling complex, high-volume and event-driven data flows.
• Own the full lifecycle – Take end-to-end accountability from data acquisition and transformation through delivery, observability, and performance.
• Set the standard – Define and enforce best practices for data modeling, CI/CD, testing, code quality, contract testing, and schema evolution.
• Solve ambiguous problems – Navigate cross-domain technical challenges and deliver solutions meeting business and technical objectives.
• Develop multi-quarter roadmaps – Translate strategic priorities into technical plans and timelines.
• Collaborate broadly – Partner with engineering, product, data science, business stakeholders, and external partner engineering teams.
• Mentor and elevate – Guide engineers through design reviews, code reviews, and mentorship.
• Evaluate and adopt – Recommend tools, platforms, and architectural patterns within the data engineering ecosystem.

Qualifications

• Bachelor's degree in a STEM field (or equivalent experience) and at least 5 years of experience in data engineering with ownership of large-scale data systems.
• Deep expertise with cloud data warehouses, preferably Snowflake, including optimization and performance tuning.
• Expert-level SQL and strong Python proficiency.
• Experience building and optimizing data pipelines and architectures using tools such as dbt, Airbyte, or Airflow.
• Experience planning and implementing enterprise data architecture across multiple systems and organizational boundaries.
• Working knowledge of queueing, batch and stream processing (Kafka, Spark, Kinesis) and scalable data stores (Apache Iceberg).
• Experience developing 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 the AWS data ecosystem 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 frameworks such as Terraform or CloudFormation.
• Experience with event-driven architecture, CDC pipelines, and low-latency operational data flows.

Benefits

• 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 program and additional wellbeing resources.