--- title: 'Senior Data Engineer at Fictiv' canonical: 'https://feeny.ai/job/senior-data-engineer-fictiv-schaumburg-qdxsktk4mn4v' type: 'job' last_seen: '2026-10-23' --- # Senior Data Engineer at Fictiv - **Company:** Fictiv - **Location:** Schaumburg, IL - **Posted:** 2026-10-23 - **Last confirmed live:** 2026-10-23 - **Apply:** https://job-boards.greenhouse.io/fictiv/jobs/8910444002 ## Job description ## About MISUMI Americas MISUMI Americas, a division of MISUMI Group, is a leading provider of standard, configurable, and custom manufacturing solutions. By integrating a vast catalog of components with a world-class digital manufacturing platform, MISUMI Americas empowers engineers and procurement teams to accelerate innovation across the entire product lifecycle. With operations in the San Francisco Bay Area and Chicago, the company serves as a vital partner for the most innovative companies in the Americas. Senior Data Engineer - Schaumburg MISUMI | Data Platform Own the data platform that MISUMI runs on MISUMI is looking for a Senior Data Engineer to be the go-to owner of our Snowflake warehouse, dbt project, and data pipelines. You will be the primary data engineer, with real ownership and real influence: the models you build and the pipelines you run are what Operations, Finance, Sales, Marketing, Engineering, Product, and Customer Support rely on to make decisions every day. You will work hands-on with a modern stack (Snowflake, dbt, Fivetran, Git/GitHub) and with AI coding agents in your daily engineering work. You will also have the autonomy to take requests from intake to production, propose what we should build next, and shape safe team practices for agentic development. If you want a role where your judgment directly determines whether the business can trust its data, this is it. Impact in this Role The Senior Data Engineer is the go-to owner of MISUMI’s Snowflake warehouse, dbt project, and data pipelines. This person turns data from business and production systems into trusted, analytics-ready models that Operations, Finance, Sales, Marketing, Engineering, Product, and Customer Support use to make decisions. Because this is the primary data engineering role, the accuracy, security, and reliability of the data platform, including regulated data such as CUI, depend on this person’s judgment and execution. Essential Functions - Administer Snowflake: manage users, roles, grants, warehouses, resource monitors and security policies, and keep the environment secure, fast and cost-efficient. - Design, build, and own dbt models (staging, intermediate, marts, and the semantic layer) that turn replicated source data into trusted, analytics-ready tables with 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. - Act as the team’s primary technical resource for modeling and pipeline work. Take requests from intake to production independently, including scoping, estimating, and reporting status. - Translate business requirements into technical requirements and data models, and bridge the gap between business teams and technology. Ask clarifying questions, agree on metric definitions and acceptance criteria with stakeholders, and turn them into specifications the team can build and test. - Proactively identify opportunities where data, modeling, or automation can help the business get closer to its goals, and propose and prioritize them with stakeholders instead of waiting for requests. - Run an impact analysis before changing, deprecating, or removing any shared table, model, or connector. Use dbt lineage, Snowflake dependency and access metadata, and stakeholder review, and document a rollback plan. - 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 speed up SQL and dbt development, testing, documentation, code review, and debugging, and help set safe team practices for using them. - Find the root cause of data-quality, performance, and pipeline problems and fix them at the source. - Tune queries, models, and warehouse usage, and 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, and explain design trade-offs to technical and non-technical stakeholders. - Evaluate new Snowflake and dbt features and tools, and recommend improvements to the data platform. - 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). Desired Traits Five core skills. Candidates must show direct, hands-on production experience in each: - Snowflake administration and engineering: access control, warehouse sizing and cost control, query tuning, clustering, security controls, cloning, time travel, and data sharing. - dbt expert modeling: layered models, dimensional modeling, incremental models, snapshots, macros, tests, documentation, and CI/CD through Git. - Advanced SQL: CTEs, window functions, recursive queries, semi-structured data, and query tuning. - ETL/ELT tooling: Fivetran (our tool) or similar, including connector setup, schema drift, deleted records, backfills, and cost. - Agentic coding and development: daily use of AI coding agents that work in the repository and terminal (not chat-only use), with disciplined verification of everything they produce. Required - 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 of hands-on Snowflake experience in production, including administration: access control, warehouse management, and 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. This includes building agentic workflows or tool integrations for data work, such as MCP servers, custom agents, or automated dbt and pipeline checks, with concrete examples of the workflows and results. - 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, or with Tableau, Looker, or a similar BI tool. - 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. Abilities - Write advanced SQL on large, complex datasets, including semi-structured data such as JSON in Snowflake VARIANT columns. - Apply data warehousing and dimensional modeling principles to turn business requirements into well-structured, maintainable models. - Work independently: take an open-ended problem, define the approach, deliver it, and raise risks early instead of stalling. - Use sound production judgment: verify before changing shared systems, plan for failure, and know how to roll back. - Use AI tools with discipline: give clear context and constraints, review and test every AI-generated change, and stay accountable for the result. - Solve hard problems methodically: break an unclear problem into testable hypotheses, gather evidence from logs, lineage, and query history, confirm the cause before changing anything, and verify the fix worked. - Communicate clearly in writing and in person, giving business context to engineers and technical context to non-engineers. Physical Demands The employee routinely sits, talks, hears, and uses hands and fingers to operate a keyboard. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Travel Ability to travel 5% annually in the US for team meetings, offsites, and conferences. Ready to own the platform? If you have run production Snowflake, dbt, and ELT at scale, you work daily with agentic coding tools, and you want to be the person the business trusts with its data, we would like to hear from you. Apply today. Salary range: $167,000 - $202,300 base salary per year, depending on experience Benefits include, but are not limited to: - Comprehensive medical and dental coverage - 401(k) plan - Generous PTO and leave programs We’re actively seeking teammates who: - Bring diverse perspectives and experience to our culture and company. - Excel at being part of a strong, empathetic team. - Thrive in an environment emphasizing respect, honesty, collaboration, and growth. - Have an ‘always learning’ mindset that celebrates learning, not just wins. - Help us continue to build a world-class organization that values the contributions of all of our teammates We encourage applications from members of underrepresented groups, including but not limited to women, members of the LGBTQ community, people of color, people with disabilities, and veterans. ## About Fictiv ## Company Overview - **One-liner**: Fictiv provides a digital operating system for custom manufacturing, connecting product creators with a global network of vetted manufacturers to source custom mechanical parts quickly and efficiently. - **Entity Type**: Private (Series E, last funding round May 2022) - **Headquarters**: San Francisco, California, United States, with additional offices in Guangzhou, China; Phoenix, Arizona; Pune, India; and Bengaluru, India - **Founded**: 2013 - **Founders**: Dave Evans and Nathan Evans ## Core Business - **Primary industry**: Custom manufacturing / Digital supply chain services - **Target customers**: B2B, serving early-stage startups to Fortune 500 enterprises across industries such as automotive, medical devices, robotics, and consumer electronics - **Mission / Purpose**: “To enable product creators to innovate” by building the world’s operating system for custom manufacturing – making it possible to build hardware at the speed of software. ## Products & Services - **Digital Manufacturing Platform**: An integrated online system for quoting, design for manufacturability (DFM) feedback, order management, and real-time tracking. Supports 3D printing, CNC machining, injection molding, and urethane casting, with lead times as fast as 1–2 days. - **Global Manufacturing Network**: A managed network of manufacturing partners across the U.S., Mexico, India, China, and Japan, offering supply chain resilience and regional sourcing flexibility. - **Technical Program Management**: Hands-on support from Fictiv engineers and program managers to guide customers from prototype through full-scale production. ## Market Standing - **Valuation / Market Cap**: Not publicly disclosed - **Key Metric**: Total funding raised – $200M (as of Series E in May 2022) - **Notable Investors/Partners**: Includes Honeywell, Intel, Bill Gates (via Gates Frontier), and other institutional investors [fictiv.com](https://www.fictiv.com/about-us) - **Growth Signals**: - Over 35 million parts manufactured to date [fictiv.com](https://www.fictiv.com/) - Served more than 5,000 companies - Expanded to four global Centers of Excellence (U.S., Mexico, India, China) to reduce supply chain risk - Active hiring across engineering, sales, and operations (51 active jobs on Greenhouse as of mid-2026) ## Competitive Advantages - **Digital-first OS for manufacturing**: Combines an automated quoting and DFM engine with a vetted global network, reducing the typical friction of custom part sourcing. - **Speed and traceability**: Parts delivered in as fast as 24 hours, with full traceability and trackability at every step. - **Global, multi-region supply chain**: Customers can choose supply regions (U.S., Mexico, India, China, Japan) to mitigate geopolitical and logistics risk. - **Enterprise-grade quality management**: Integrated quality control and program management support, appealing to Fortune 500-level production requirements. ## Strategic Focus - **Scaling global manufacturing hubs**: Expanding in-region Centers of Excellence to offer faster, lower-risk production close to customers. - **AI and automation**: Using artificial intelligence to accelerate quoting, DFM feedback, and supply chain decisions (including in employment decisions for internal operations). - **Deepening enterprise relationships**: Targeting large OEMs and regulated industries (medical, aerospace, automotive) with compliance and traceability features. - **Platform ecosystem**: Enhancing the digital platform with new materials, finishes, and real-time analytics to further reduce time-to-market for hardware innovators. ## Why Work Here - **Culture & values**: Emphasizes a “Service Mentality” (value #2), collaboration, diversity, and autonomy. Described as a passionate team across multiple global offices. - **Work policy**: Remote-friendly environment with systems to keep distributed teams connected. Offices in San Francisco, Guangzhou, Phoenix, Pune, and Bengaluru. - **Perks and benefits**: - Monthly virtual work stipend - Wellness perks - Paid volunteer days - Learning and development stipend (Udemy Business courses, continued education stipends) - Leadership coaching for high performers - Paid parental leave - Equity options - **Engineering culture**: Access to modern tools (Salesforce, data engineering, integrations) and direct exposure to executive leadership; strong focus on career growth and autonomy. ## Sources 1. [Fictiv Careers Page](https://www.fictiv.com/careers) 2. [Fictiv Main Website](https://www.fictiv.com/) 3. [Fictiv About Us Page](https://www.fictiv.com/about-us) 4. [Crunchbase – Fictiv](https://www.crunchbase.com/organization/fictiv) 5. 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