
Staff Data Analytics Engineer
Required skills
- data pipelines
- transformation layers
- modeled datasets
- tested datasets
- documented datasets
- data contracts
- data quality
- monitoring
- version control
- code quality
Nice to have
- BI platform migration
- Ruby on Rails
- Domo
- proprietary BI platform
Role summary
CareerPlug is seeking a Staff Data Analytics Engineer to own the middle of their data stack, transforming raw data into reliable, modeled, and tested datasets. This senior individual contributor role will define core business metrics, establish data contracts between the warehouse and their Rails application, and design data quality practices. The engineer will also set technical direction for the data function, evaluate tooling, and mentor teammates. The position requires strong SQL, data modeling, data quality, and software engineering practices applied to data. Experience with BI tooling migration and Ruby on Rails is preferred. This is a fully remote, US-based position with a base salary of $165,000 plus bonus potential.
We believe that people are the heart of our business and are committed to building one of the best places to work – anywhere. To us, that means putting care and purpose into our hiring process, providing meaningful development and training opportunities for our team members, and living our core values every day.
CareerPlug is proud to be an equal opportunity employer committed to fostering a diverse team. Our executive team takes responsibility for creating a safe and welcoming environment built on inclusion and respect for all.
Why this role existsWe turn business logic into software. This Staff Data Analytics Engineer role owns the middle of our data stack: taking raw data and turning it into modeled, tested, documented datasets that our business and product teams can build on with confidence.
You’ll be our only dedicated data engineer and the senior-most technical seat in our data function. You’ll work closely with our BI team and our tight-knit Product & Engineering function to set the patterns other analytics work operates within, define what our core metrics actually mean, and create a stable interface between our warehouse and our Rails application so analytics logic and product code can evolve without breaking one another.
The near-term work includes helping us evaluate and potentially even lead a transition away from a proprietary BI platform where important business logic currently lives in ways that are difficult to test, version, and share with application engineers. You’ll help set the direction for what comes next. The long-term work is everything after that: the definitions, tests, contracts, pipelines, and engineering craft that make trustworthy data possible.
This is not a cloud infrastructure role. Our Platform team owns the warehouse infrastructure, scheduler, access, and related platform operations. We’re hiring for the layer above that: the data architecture, transformations, contracts, and software practices that turn infrastructure into dependable business and product data.
What you’ll do
- Own the architecture and reliability of data pipelines that bring complete, timely data into the warehouse.
- Build and maintain modeled, tested, documented datasets that teams can trust and safely change.
- Define and steward core business metrics and entities so important numbers have one clear, discoverable definition.
- Create and maintain stable data contracts between the warehouse and our Rails application.
- Design data quality practices that catch issues early, including testing, monitoring, freshness expectations, and incident follow-up.
- Own and improve operational data writebacks and system-to-system syncs.
- Partner with BI teammates and business stakeholders to understand the business domain behind the data.
- Set technical direction for our data function, weighing architecture and tooling decisions for maintainability, cost, scalability, and future needs.
- Write and review production-quality code, documentation, and pull requests that other engineers can safely extend.
- Use AI coding tools thoughtfully while maintaining accountability for quality, security, testing, and maintainability.
- Published datasets and metrics are trusted enough that stakeholders can act on them without maintaining competing versions.
- Core metrics have a single live definition, and documentation answers common data questions without requiring a person to interpret them every time.
- Data incidents caused by unexpected schema or dataset changes are rare, quickly detected, and leave behind stronger safeguards.
- Application engineers understand which datasets are stable interfaces they can build against and which are internal implementation details.
- Our BI and engineering teammates experience the data platform as deliberate, maintainable, and increasingly easier to work with over time.
- You’re strongest in the middle of the data stack: transforming raw data into reliable, well-modeled datasets and interfaces that others can build on.
- You have deep SQL skills and strong judgment around data modeling, testing, documentation, version control, and production data quality.
- You’ve worked with modern data and BI ecosystems and can evaluate tools based on the problem they solve rather than attachment to a particular vendor.
- You’re comfortable leading through ambiguity and can explain technical tradeoffs clearly.
- You think like a software engineer about data: code quality, maintainability, contracts, tests, incremental changes, and future maintainers all matter to you.
- You can move between technical and business conversations and translate business meaning into durable data definitions.
- You enjoy being a senior individual contributor who influences through technical judgment, collaboration, mentoring, and standards rather than people management.
- You use AI-assisted engineering intentionally without lowering the bar for what ships.
- Demonstrated experience designing and maintaining production data pipelines and transformation layers.
- Strong SQL and relational data modeling experience.
- Experience with automated testing, version control, code review, and software engineering practices applied to analytics/data work.
- Experience defining or governing shared metrics, semantic concepts, or trusted datasets used across teams.
- Experience integrating data systems with applications, APIs, or operational workflows.
- Experience participating in or leading a BI/data tooling migration is strongly preferred.
- Experience with Ruby on Rails or another backend application framework is a plus.
- Experience with Domo or another proprietary BI platform is helpful, but not required.
- Work from home (we're fully remote)
- Employer-Paid Health Insurance
- Unlimited PTO (with minimums!)
- Pet Insurance
- One-week paid PTO (pre-start date)
- 401(k) Company Match
- Employer-Paid Life Insurance
- Employer-Paid Long-Term Disability Insurance
- Donation Matching
- Home Office Stipend
CareerPlug believes in equitable and transparent compensation practices. All our employees have access to what every role pays at the company. We post compensation on all our job postings. In order to ensure equity and fairness for candidates and current employees, we always lead at our best and don’t negotiate offers. Read more about our compensation philosophy here.
Remote-first: We’re fully remote in the U.S. Occasional travel to company/team events as needed and at least one optional in-person company event annually. This role may be filled by any U.S.-based candidate.
This is a remote position.
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