Job description

Company Summary Zoro.com is a leading eCommerce platform offering nearly 12 million tools, parts and supplies for our business customers. Launched in 2011, we brought a B2C-like experience to the B2B industry, and continue to be at the forefront of digital innovation at the intersection of technology and distribution. We have rapidly grown to over $1 billion in annual revenue and we’re just getting started! About the Role Join a data organization that is becoming a software-engineering organization and is deliberately reinventing how engineering work is performed with AI. This is a software engineering role in the data domain. You will build APIs, backend services, shared libraries, operational data stores, and data-processing systems that power internal and customer-facing capabilities. This is not a traditional ELT/ETL data engineer role. The emphasis is on software engineering, not warehouse SQL or orchestration alone. Experience with BigQuery, Airflow, or similar tools is useful, but not sufficient by itself. We welcome software engineers with strong fundamentals and enough familiarity with data systems to learn the rest. You will work on a small team within Zoro’s data organization, alongside product engineering and platform engineering. You will own systems, participate in design reviews, deploy and operate what you build, and take part in an on-call rotation. AI-assisted engineering is a core part of how we work. We do not expect mastery. We do expect active experimentation, enthusiasm, and a willingness to keep improving. You should be using AI to test designs, find underspecified requirements, break work into tasks and dependencies, explore unfamiliar code, and create artifacts that people and AI tools can use to review and execute work. You should also be experimenting with different tools and approaches and developing opinions about what works well for which kinds of tasks. If you are excited about AI-assisted engineering, you will find a team learning quickly and sharing what works. If you do not want AI to be part of your regular engineering practice, this role is unlikely to be a fit. What You Will Do Build and maintain production APIs, backend services, libraries, operational data stores, and data-processing applications. Participate in system design, design reviews, and technical tradeoff discussions. Design clear interfaces, service boundaries, schemas, and data contracts. Write modular, testable, observable, and maintainable software. Own systems through deployment, monitoring, incident response, maintenance, and retirement. Build reliable systems that handle retries, schema changes, duplicate events, partial failures, and unexpected inputs. Use AI throughout design, planning, implementation, testing, review, and codebase exploration. Validate AI-generated output and remain responsible for understanding and operating what you ship. Share useful AI workflows, experiments, and lessons with the team. Participate in on-call and improve systems based on production experience. An Excellent Candidate Has Experience building backend services, internal platforms, developer tools, or distributed applications. Experience designing APIs and operational databases. Familiarity with asynchronous processing, queues, event-driven systems, or change-data capture. Experience handling idempotency, retries, concurrency, and backward compatibility. Familiarity with cloud infrastructure, containers, CI/CD, infrastructure as code, and observability. Experience with data pipelines, analytical systems, data modeling, or large-scale data movement. A habit of documenting AI experiments and developing repeatable workflows. Experience using AI to critique designs, find missing requirements, navigate codebases, generate tests, or evaluate implementation options. Practical opinions about where AI tools are useful, where they are unreliable, and how to improve their output. How We Work We value engineers who take ownership, prefer simple systems, treat operations as part of engineering, ask questions when designs are unclear, give thoughtful feedback, and balance speed with reliability. We also expect engineers to use AI aggressively but not uncritically, and to share what they learn so the whole team improves. Qualifications Education: Bachelor's or Master's degree in Computer Science, Applied Mathematics, Engineering, or a related field, or equivalent practical experience. Experience: Minimum 5 years of experience in data engineering or software development, with a track record of designing and delivering production data systems. Table Stakes: Experience building, shipping, and operating production software. Strong programming skills in at least one general-purpose language. Meaningful programming experience beyond SQL. Understanding of modular design, APIs, testing, error handling, and maintainability. Working knowledge of relational data concepts, including schemas, keys, transactions, and data integrity. Experience with unit and integration testing and diagnosing production failures. Willingness to own systems and participate in on-call. Ability to contribute to design reviews and explain technical decisions clearly. Active use of AI for more than code completion. Sound judgment when evaluating AI-generated output. A bachelor’s degree in a relevant field or equivalent practical experience. Soft Skills: Technical Leadership: Influences team architecture and engineering practices. Initiates improvements without being asked. Communication: Coordinates complex integrations across adjacent teams. Drafts design proposals and RFC documents clearly. Mentorship: Guides junior engineers through data design patterns, system thinking, and AI-assisted development practices. Product Thinking: Leads data products as first-class assets with consumer SLAs, versioning, and lifecycle ownership. Judgment: Makes sound technical tradeoff decisions. Balances delivery velocity with long-term code health. Total Rewards Zoro’s total compensation plan includes our Zoro Incentive Plan (ZIP) that is designed to foster and reward our team members for strong performance. Total compensation will be highly competitive. In addition to competitive compensation, Zoro offers comprehensive benefits and perks including: Medical, dental, vision, and life insurance plans with coverage starting on day one of employment Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents. We also support growing your family through access to adoption assistance program 6 free sessions each year with a licensed therapist and Wellhub portal membership to support your mental and emotional wellbeing At least 18 paid time off days annually for full-time employees and 6 company holidays per year 6% company contribution to a 401K Retirement Savings Plan each pay period, no employee contribution required Tuition reimbursement, student loan refinancing and access to financial counseling, education, and tools Charitable Gift Program - match gift to an eligible educational, cultural, community health, and human service organizations Employee discounts and admission to various civic and cultural institutions around Chicago Zoro office perks including coffee bar, beer on tap, unlimited snacks, access to the onsite gym, and incredible city skyline views For additional information and details regarding our benefits and our parent company, W. W. Grainger, please click on the link here . The pay range provided is not a guarantee of compensation. The range listed reflects the expected base pay for this position at the time of posting, based on the role's job grade. Actual compensation may vary depending on factors such as location, relevant experience and individual qualifications. Illinois $105,100 — $175,100 USD Our Culture Zoro was founded in 2011 with a simple idea: make it easy for businesses to get the tools, parts, and supplies they need to keep things running. We've grown by staying curious, moving quickly, and solving everyday challenges in smart, practical ways. Backed by W.W. Grainger and inspired by our endless assortment business model, we’re on a clear path toward our next big milestone: $2 billion in revenue—and beyond. At Zoro, we don’t just follow a playbook—we help build it. You’ll get to work on real problems with a supportive team that shares ideas freely, learns from each other, and celebrates wins together. Our culture is grounded in values that guide how we show up every day: Winning & Learning Together , Being Customer Obsessed , Being Transparent , and Taking Ownership . We don’t have all the answers, but we’re always asking good questions. Zoro’s culture has been recognized by Fortune, Best Places to Work, and Built In Chicago—but the recognition we care about most comes from our team members, who make this place what it is. We also know that flexibility matters. Our hybrid work model gives you space to focus and the flexibility to live your life — asking team members to be onsite at least two days a week. Our Chicago HQ (right above Ogilvie Transportation Center in the Accenture Tower) is always open and ready for connection, collaboration, or just a good cup of coffee. At Zoro, we’re growing fast toward big aspirations — and we’re continuously excited about the new challenges we get to solve together. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, protected veteran status, or any other protected characteristic under federal, state, or local law. We are proud to be an equal opportunity workplace. We are also committed to fostering an inclusive, accessible work environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one’s employment. Should you need a reasonable accommodation during the application and selection process, including, but not limited to use of our website, any part of the application, interview, or hiring process, please advise us so that we can provide appropriate assistance.

Requirements

Must-haves

Company Summary
Join a data organization that is becoming a software-engineering organization and is deliberately reinventing how engineering work is performed with AI.
AI-assisted engineering is a core part of how we work. We do not expect mastery. We do expect active experimentation, enthusiasm, and a willingness to keep improving.
If you are excited about AI-assisted engineering, you will find a team learning quickly and sharing what works. If you do not want AI to be part of your regular engineering practice, this role is unlikely to be a fit.
Build and maintain production APIs, backend services, libraries, operational data stores, and data-processing applications.
Participate in system design, design reviews, and technical tradeoff discussions.
Design clear interfaces, service boundaries, schemas, and data contracts.
Write modular, testable, observable, and maintainable software.
Own systems through deployment, monitoring, incident response, maintenance, and retirement.
Build reliable systems that handle retries, schema changes, duplicate events, partial failures, and unexpected inputs.
Use AI throughout design, planning, implementation, testing, review, and codebase exploration.
Validate AI-generated output and remain responsible for understanding and operating what you ship.
Share useful AI workflows, experiments, and lessons with the team.
Participate in on-call and improve systems based on production experience.
An Excellent Candidate Has
Experience building backend services, internal platforms, developer tools, or distributed applications.
Experience designing APIs and operational databases.
Familiarity with asynchronous processing, queues, event-driven systems, or change-data capture.
Experience handling idempotency, retries, concurrency, and backward compatibility.
Familiarity with cloud infrastructure, containers, CI/CD, infrastructure as code, and observability.
Experience with data pipelines, analytical systems, data modeling, or large-scale data movement.
A habit of documenting AI experiments and developing repeatable workflows.
Experience using AI to critique designs, find missing requirements, navigate codebases, generate tests, or evaluate implementation options.
Practical opinions about where AI tools are useful, where they are unreliable, and how to improve their output.

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Keywords to mirror

aisqlrestci/cd

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off