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 auditability.
- Build and optimize reliable batch, streaming, and event-driven pipelines, data models, and data 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 implementation methods and timelines.
- Collaborate with engineering, product, analytics, machine learning, business, and partner engineering teams.
- 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.
- Deep expertise with cloud data warehouses, especially Snowflake, including optimization and performance tuning.
- Expert-level SQL and strong Python proficiency, with the ability to learn additional languages.
- Hands-on experience with data pipelines, architectures, and datasets using tools such as dbt, Airbyte, or Airflow.
- Experience implementing enterprise data architecture across multiple systems, domains, and organizational or partner boundaries.
- Working knowledge of queueing, batch and stream processing, including Kafka, Spark, and Kinesis, plus scalable data stores such as Apache Iceberg.
- Experience building database-heavy services or APIs with testability and maintainability in mind.
- Experience with automated testing, contract testing, schema evolution, CI/CD, and data pipeline quality practices.
- Strong knowledge of the AWS data ecosystem and cloud-native infrastructure.
- Experience integrating PLM, ERP, or enterprise SaaS systems; Teamcenter, BMIDE, Active Workspace APIs, or AWC integrations are strong advantages.
- Familiarity with data visualization tools such as Looker and Streamlit.
- Experience with data governance, data quality frameworks, observability tooling, event-driven architecture, CDC pipelines, and low-latency operational data flows.
- Exposure to lakehouse or data mesh architectures and infrastructure-as-code tools such as Terraform or CloudFormation.
- Manufacturing, supply chain, or marketplace experience is a plus.
Benefits
- Competitive benefits package including a 401(k) match.
- Medical, dental, and vision insurance.
- Life and disability insurance.
- Paid time off including vacation, sick leave, floating holidays, fixed holidays, maternity leave, and bonding leave.
- Employee assistance program and other wellbeing resources.
- Hybrid work arrangement is indicated by the posting’s #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.