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Salary: USD 167,000 - 202,300 / annual
MISUMI Americas, a division of MISUMI Group, is a leading provider of standard, configurable, and custom manufacturing solutions. They operate a digital manufacturing platform serving innovative companies across the Americas, with offices in the San Francisco Bay Area and Chicago.
You will be the primary owner of MISUMI's Snowflake data warehouse, dbt project, and data pipelines. This is a high-impact individual contributor role where the models you build and pipelines you operate directly support decision-making across Operations, Finance, Sales, Marketing, Engineering, Product, and Customer Support. You will work hands-on with a modern stack (Snowflake, dbt, Fivetran, GitHub) and integrate AI coding agents into your daily engineering workflow.
Key responsibilities include:
- Administer and optimize Snowflake: manage users, roles, grants, warehouses, resource monitors, and security policies to ensure the environment is secure, fast, and cost-efficient.
- Design, build, and own layered dbt models (staging, intermediate, marts, semantic layer) that transform replicated source data into trusted, analytics-ready tables with comprehensive tests and documentation.
- Build, operate, and monitor ELT pipelines from production and business systems into Snowflake using Fivetran and related tools; resolve connector failures, schema changes, backfills, and data-quality issues.
- Take requests from intake to production independently, including scoping, estimating, and reporting status.
- Translate business requirements into technical specifications and data models; bridge the gap between business teams and technology by clarifying requirements, defining metrics, and establishing acceptance criteria.
- Proactively identify opportunities where data, modeling, or automation can advance business goals and propose them to stakeholders.
- Conduct impact analysis before changing, deprecating, or removing shared tables, models, or connectors; use dbt lineage, Snowflake metadata, and stakeholder review; document rollback plans.
- Own the Git and GitHub workflow for the dbt project: branching standards, pull-request review, automated tests, and deployment.
- Use AI assistants and agentic workflows in daily engineering work to accelerate SQL and dbt development, testing, documentation, code review, and debugging; help establish safe team practices for agentic development.
- Diagnose and fix root causes of data-quality, performance, and pipeline problems.
- Tune queries, models, and warehouse usage; advise engineers and analysts on efficient query patterns and table design.
- Maintain data dictionaries, data-flow diagrams, and schema documentation.
- Lead data design sessions and technical reviews; explain design trade-offs to technical and non-technical stakeholders.
- Evaluate new Snowflake and dbt features and recommend platform improvements.
- Mentor analysts and engineers on SQL and dbt best practices.
- Work with remote, cross-functional teams across time zones.
- Maintain and contribute to the Quality Management System (QMS).
Travel: 5% annually in the US for team meetings, offsites, and conferences.
REQUIREMENTS:
- Bachelor's degree in Data Science, Computer Science, Information Systems, or related field, or equivalent practical experience.
- 10+ years of experience as a data engineer, designing, building, and operating data pipelines and warehouses.
- 6+ years of hands-on Snowflake experience in production, including administration (access control, warehouse management, cost and 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 working with ETL/ELT tools such as Fivetran, Airbyte, Stitch, Matillion, Informatica, or Talend, plus experience with pipeline orchestration.
- Demonstrated, hands-on experience using agentic coding tools that work directly in the codebase (not chat-only AI use) in daily data engineering work, including building agentic workflows or tool integrations for data work (MCP servers, custom agents, automated dbt and pipeline checks) with concrete examples.
- 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 data platforms that hold regulated data (such as 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.
PREFERRED:
- Direct Fivetran experience, including connector management.
- Experience with Sigma Computing, Tableau, Looker, or similar BI tools.
- Experience modeling ERP and 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, such as Terraform.
- Background in manufacturing, supply chain, or marketplace businesses.
