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Wiraa

Data Engineer

Canada

Job type: Full-time
Experience: Minimum of 5 years of experience in data engineering or related roles
Posting language: English
Posted: Oct 1, 2026

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Original job description

About The Company

Xometry (NASDAQ: XMTR) is a leading digital manufacturing marketplace that connects innovative ideas with manufacturing capabilities worldwide. By leveraging its advanced online platform, Xometry provides critical resources to manufacturers, enabling them to expand their operations and reach new markets. Simultaneously, it offers Fortune 1000 companies and other buyers seamless access to a vast network of manufacturing partners, facilitating efficient sourcing of custom parts and components. Xometry’s commitment to innovation and quality positions it as a pivotal player in transforming how manufacturing services are delivered in today’s rapidly evolving industrial landscape.

About The Role

We are seeking a highly skilled Staff Data Engineer to join our Data Platform team. This senior individual contributor role demands a broad technical scope and a significant organizational impact. The successful candidate will be responsible for defining data architecture strategies, designing scalable data pipelines, and establishing best practices for data systems operation. A key focus will be owning the data architecture behind strategic initiatives such as the DFM AI + IQE integration with our partner ecosystem. This involves building and maintaining the digital thread that connects Xometry’s platform with partner systems like Solid Edge, NX, Designcenter, and Teamcenter, ensuring real-time data flow for quotes, manufacturability signals, and pricing feedback. The role offers an exciting opportunity to influence core data infrastructure, drive innovation, and collaborate across multiple teams to enable high-quality, fast-paced decision-making processes that are central to our business growth and technological advancement.

Qualifications

Bachelor’s degree in a STEM field or equivalent experience
Minimum of 5 years of experience in data engineering or related roles
Deep expertise with cloud data warehouses, preferably Snowflake, including optimization and performance tuning
Proficiency in SQL and Python; ability to learn additional languages as needed
Hands-on experience designing and optimizing data pipelines, architectures, and datasets using tools like dbt, Airbyte, Airflow, or similar
Strong understanding of enterprise data architecture, including integrations across multiple systems and domains
Knowledge of queueing, batch, and stream processing technologies such as Kafka, Spark, or Kinesis
Experience with scalable data stores like Apache Iceberg
Proficiency in building database-heavy services and APIs with a focus on testability and maintainability
Solid understanding of CI/CD principles, automated testing, schema evolution, and contract testing
Experience with AWS cloud infrastructure and native data services
Ability to operate independently, evaluate ambiguous problems, and communicate effectively at all organizational levels
Enterprise or partner system integration experience, especially with PLM, ERP, or SaaS platforms; familiarity with Teamcenter or similar PLM systems is a plus
Familiarity with data visualization tools such as Looker or Streamlit
Experience with data governance, data quality frameworks, and observability tools
Exposure to lakehouse or data mesh architectural patterns
Knowledge of infrastructure as code frameworks like Terraform or CloudFormation
Experience with event-driven architecture, CDC pipelines, and low-latency operational data flows
Interest or experience in manufacturing, supply chain, or marketplace environments is advantageous but not mandatory

Responsibilities

Lead the design and implementation of enterprise-scale data architecture and engineering solutions across multiple systems and domains
Own the partner integration data plane, including architecting bidirectional pipelines and data models for parts, BOMs, quotes, and manufacturability signals
Develop scalable batch and streaming data pipelines to handle high-volume, real-time data flows
Manage the full lifecycle of data engineering tasks - from data acquisition and transformation to delivery, observability, and performance monitoring
Define and enforce best practices for data modeling, CI/CD, testing, and schema evolution, especially for partner boundary crossings
Address complex cross-domain technical challenges by evaluating variables and delivering solutions aligned with business and technical goals
Create multi-quarter technical roadmaps translating strategic priorities into actionable plans with clear timelines
Collaborate with engineering, product, analytics, and partner teams to develop robust technical solutions based on business requirements
Mentor other engineers through design and code reviews, fostering team growth and technical excellence
Stay current with evolving data engineering tools, platforms, and architectural patterns, and recommend adoption strategies

Benefits

Competitive annual salary ranging from $180,000 to $200,000, supplemented by performance-based bonuses
Comprehensive health benefits including medical, dental, and vision insurance
Retirement plan with 401(k) match
Generous paid time off including vacation, sick leave, holidays, and parental leave
Life and disability insurance coverage
Employee assistance programs and wellbeing resources
Opportunities for professional development and career growth within a dynamic, innovative environment

Equal Opportunity

Xometry is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants. All employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected characteristic. We ensure a fair and respectful workplace where everyone can thrive.

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More about this job

Responsibilities

Lead enterprise-scale data architecture and engineering across systems, including bidirectional partner integrations for parts, bills of materials, quotes, and manufacturability signals. Build and operate scalable batch and streaming pipelines, establish engineering standards and roadmaps, and collaborate with teams and partners while mentoring engineers.

Requirements

Requires a bachelor’s degree in a STEM field or equivalent experience and at least five years of experience in data engineering or a related role. Candidates should have strong SQL and Python skills, cloud data warehouse and AWS experience, expertise in scalable data pipelines and enterprise integrations, and familiarity with testing, CI/CD, streaming technologies, and data architecture.

Skills

Data Architecture
Data Engineering
SQL
Python
Snowflake
Data Pipelines
dbt
Airbyte
Airflow
Kafka
Spark
AWS
Apache Iceberg
CI/CD
Data Modeling
Enterprise System Integration

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off
Parental Leave
Life Insurance
Disability Insurance
Employee Assistance Programs
Wellbeing Resources
Professional Development
Career Growth Opportunities
Performance-Based Bonuses

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Data Architecture
Snowflake
SQL
Python
AWS
dbt
Airbyte
Airflow
Kafka
Spark
Kinesis
Apache Iceberg
CI/CD
Automated Testing
Schema Evolution
Contract Testing
Data Modeling
Data Governance
Data Quality
Data Observability
Terraform
CloudFormation
Event-Driven Architecture
Change Data Capture
Streaming Data
Batch Processing
PLM
ERP
Teamcenter

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