Senior Data Engineer

MISUMI Americas is seeking a Senior Data Engineer to take ownership of the company’s Snowflake data warehouse, the dbt project, and the ELT data pipelines that keep analytics models reliable and ready for consumption. This onsite role in Schaumburg, IL focuses on building trusted, analytics-ready structures while strengthening security, accuracy, and operational stability, including support for regulated data environments.

Role Focus

• Own MISUMI’s Snowflake warehouse administration, including security and cost/performance controls.
• Design and maintain dbt models that produce staging, intermediate, marts, and a semantic layer with tests and documentation.
• Build, operate, and monitor ELT pipelines that move data from production and business systems into Snowflake using Fivetran and related tooling.
• Serve as a primary technical resource from intake to production, handling scoping, estimating, and status reporting.
• Use impact analysis and dependency-aware review before changing, deprecating, or removing shared assets.

Key Responsibilities

• Administer Snowflake: manage users, roles, grants, warehouses, resource monitors, and security policies to keep the environment secure, fast, and cost-efficient.
• Develop dbt: build and maintain models (staging, intermediate, marts, semantic layer) that transform replicated source data into trusted, analytics-ready tables, including tests and documentation.
• Operate ELT: resolve connector failures, handle schema changes, manage backfills, and address data-quality issues for pipelines into Snowflake.
• Bridge business and engineering: translate business requirements into technical requirements and data models, align on metric definitions and acceptance criteria, and convert them into buildable specifications.
• Proactively propose improvements: identify opportunities where data, modeling, or automation can move the business toward goals and prioritize with stakeholders.
• Manage change safely: run impact analysis before altering shared tables/models/connectors, use dbt lineage and Snowflake dependency/access metadata, review with stakeholders, and document a rollback plan.
• Own the dbt Git workflow: branching standards, pull-request review, automated tests, and deployment.
• Integrate and apply agentic tooling in daily engineering: use AI assistants and agentic workflows to accelerate SQL/dbt development, testing, documentation, code review, and debugging, while establishing safe team practices.
• Troubleshoot and improve: find root causes of data-quality, performance, and pipeline issues and fix them at the source.
• Optimize performance: tune queries/models/warehouse usage and advise engineers and analysts on efficient query patterns and table design.
• Maintain documentation: keep data dictionaries, data-flow diagrams, and schema documentation current.
• Lead reviews: run data design sessions and technical reviews and explain design trade-offs to technical and non-technical stakeholders.
• Evaluate platform improvements: assess new Snowflake/dbt features and recommend enhancements to the data platform.
• Mentor others on SQL and dbt best practices.
• Collaborate with remote, cross-functional teams across time zones.
• Maintain and contribute to the Quality Management System (QMS).

Minimum Qualifications

• Bachelor’s degree in Data Science, Computer Science, Information Systems, or a related field, or equivalent practical experience.
• 10+ years of experience as a data engineer designing, building, and operating data pipelines and warehouses.
• 6+ years hands-on Snowflake experience in production, including administration: access control, warehouse management, and cost/performance monitoring.
• 5+ years building and maintaining production dbt projects (dbt Core or dbt Cloud), including testing, documentation, incremental models, macros, and CI/CD.
• 5+ years with ETL/ELT tools such as Fivetran, Airbyte, Stitch, Matillion, Informatica, or Talend, including pipeline orchestration experience.
• Demonstrated, hands-on experience using agentic coding tools that work directly in the codebase (not chat-only AI use), including building agentic workflows or tool integrations for data work.
• Expert SQL, including CTEs, window functions, and performance tuning.
• Daily use of Git and GitHub pull-request workflows.
• Experience being the primary or sole owner of a data platform, or the technical lead for one.
• Experience administering platforms with regulated data (for example, CUI under NIST SP 800-171), including access control, audit logging, encryption, and data classification. Must be able to pass a background check and complete required CUI and security training.

Technologies

• Snowflake, dbt, dbt Core, dbt Cloud
• Fivetran, Airbyte, Stitch, Matillion, Informatica, Talend
• Git, GitHub
• AI coding agents, MCP servers
• SQL, JSON
• NIST SP 800-171

Benefits

• Comprehensive medical and dental coverage
• 401(k) plan
• Generous PTO and leave programs

Preferred Qualifications

• Direct Fivetran experience, including connector management.
• Experience with Sigma Computing, or with Tableau, Looker, or similar BI tools.
• Experience modeling ERP/CRM data such as NetSuite or Salesforce.
• Python for data tooling and automation.
• Snowflake SnowPro certification or dbt certification.
• Infrastructure-as-code experience for Snowflake (for example, Terraform).
• Background in manufacturing, supply chain, or marketplace businesses.

Additional Details

• Salary: USD 167,000 - 202,300 per year
• Location: Schaumburg, IL (onsite)
• Travel: Ability to travel 5% annually in the US for team meetings, offsites, and conferences.
• Physical demands: Routinely sits, talks, hears, and uses hands and fingers to operate a keyboard; reasonable accommodations may be made for individuals with disabilities.