5 months ago
Base Salary
$180k - $200k/yr
Responsibilities
- Design and drive enterprise-scale data architecture and engineering solutions across multiple systems and domains.
- Architect and build the partner integration data plane, including bidirectional pipelines, joint data models, low-latency signal paths, governance, lineage, and audit capabilities.
- Build and optimize reliable batch, streaming, event-driven, and real-time data pipelines, models, and platforms.
- Own the full data engineering lifecycle from acquisition and transformation through delivery, observability, and performance optimization.
- Define and enforce standards for data modeling, CI/CD, testing, contract testing, schema evolution, and code quality.
- Develop multi-quarter technical roadmaps and independently determine methods and timelines for complex assignments.
- Collaborate with engineering, product, data science, business, and partner engineering teams to deliver technical solutions.
- Mentor engineers through design reviews, code reviews, and technical guidance.
- Evaluate data engineering tools, platforms, and architectural patterns.
Requirements
- Bachelor’s degree in a STEM field or equivalent experience, plus at least 5 years of experience in a data engineering-related role.
- Demonstrated ownership of complex, large-scale data systems and enterprise data architecture across multiple systems and domains.
- Deep expertise with cloud data warehouses, with Snowflake strongly preferred, including optimization and performance tuning.
- Expert SQL skills and strong Python proficiency, with the ability to learn additional languages as needed.
- Hands-on experience building and optimizing data pipelines, architectures, and datasets using tools such as dbt, Airbyte, or Airflow.
- Working knowledge of queueing, batch and stream processing, and scalable data stores such as Kafka, Spark, Kinesis, and Apache Iceberg.
- Experience writing database-heavy services or APIs and designing for testability and maintainability.
- Experience with automated testing, contract testing, schema evolution, data governance, data quality frameworks, and observability tooling.
- Strong understanding of the AWS data ecosystem and cloud-native infrastructure.
- Experience integrating with PLM, ERP, or enterprise SaaS systems; Teamcenter experience or comparable PLM exposure is preferred.
- Familiarity with data visualization tools such as Looker and Streamlit.
- Exposure to lakehouse or data mesh architectures, infrastructure as code, event-driven architecture, CDC pipelines, and low-latency operational data flows.
- Experience in manufacturing, supply chain, or marketplace environments is a plus.
- Ability to operate independently on ambiguous assignments and communicate effectively with internal and external stakeholders.
Benefits
- Estimated base salary is $180,000-$200,000 annually, plus commission depending on relevant factors.
- Competitive benefits package including a 401(k) match, medical, dental, and vision insurance.
- Life and disability insurance are provided.
- Paid time off includes vacation, sick leave, floating holidays, fixed holidays, maternity leave, and bonding leave.
- Employee assistance and other wellbeing resources are available.
- The role is hybrid, as indicated by the #LI-Hybrid designation.
Tech Stack
Categories
Data Engineering
About Xometry
Xometry builds an AI-enabled marketplace that connects engineers and procurement teams with a vetted global network of manufacturers for on-demand CNC machining, 3D printing, sheet metal, and injection molding. The company earns fees by brokering instant-quote RFQs and managing production, logistics, and quality across its supplier base. Founded in 2013, Xometry is a publicly traded company (NASDAQ: XMTR) based in the Washington, DC–Baltimore area and serves buyers from startups to Fortune 1000 firms.