QA Engineer

Everything happens somewhere - which is why spatial analytics is fundamental to companies trying to understand the “where” and the “why” of their business. CARTO is the leading Location Intelligence platform, empowering companies with scalable and cloud-native spatial analytics. CARTO helps organizations make better business decisions by empowering data analysts, business analysts, GIS professionals, and developers with faster, more flexible, and more secure spatial data analysis and visualization tools. Whether through optimizing network planning, assessing risk, identifying growth opportunities, or other use cases, companies benefit from turning their location data into business value.

With an exceptionally diverse team of 150 people spread across the US and Europe, CARTO (backed by Insight Partners, Accel Partners, Salesforce Ventures, and Earlybird Ventures, among others) is changing the way companies analyze location data - making it simple to do this straight out of modern, cloud data warehouses. Redefining its category, the company has grown rapidly in recent years providing a compelling alternative to legacy GIS software.

To continue this growth, the engineering team is looking for an enthusiastic and ambitious Software Engineer in Test to work on the end-to-end quality of our platform.

Location: The position is based in Spain. We do have offices in Madrid and Seville, but we're open to candidates based anywhere in Spain.

Key Responsibilities

• Build AI tooling that turns requirements, specs and tickets into test plans and executable test cases

• Use AI agents to write, extend and repair automated tests — and own the judgment call on what they produce: the plausible-but-wrong test, the assertion that can never fail, the coverage that only looks like coverage. This is the core skill of the job.

• Automate execution: suites that run on every change, stay fast, don't flake, and fail in a way someone can diagnose without re-running them locally

• Work with Development and Product Management as their quality partner — help engineers test their own features properly, review test coverage on PRs, stop regressions before production

• Convert manual test cases into automated ones, and keep an honest inventory of what's left and why

• Run the manual testing that still needs a human: exploratory passes on new features, visual and cartographic correctness, complex data flows across data warehouses

• Build the test data the automation depends on — datasets, warehouse connections, maps consuming multiple data sources

• Get deep enough in spatial SQL to validate our analysis output yourself

You offer

• Hands-on use of AI coding assistants (Claude Code, Copilot, Cursor) as a daily working tool, and concrete examples of where they've burned you

• Comfortable writing and debugging TypeScript or JavaScript; you can read the code you're testing

• Playwright, Cypress or a similar modern E2E framework

• API testing experience

• Experience working with SQL — you can query and validate data yourself

• Clear written communication in English; much of this job is explaining risk to developers and PMs

• Experience building AI-driven test tooling — agentic test generation, LLM-based assertions, self-healing selectors, AI-assisted triage

• Nice to have: experience testing GIS or mapping software, CI/CD pipelines (ideally GitHub Actions), BDD/TDD practice or Gherkin, and querying data warehouses like BigQuery, Snowflake, Databricks or Redshift

• +3 years in QA or test automation on a real product

• A track record of automating what used to be manual — the thing we'll dig into most

• The instinct to ask what isn't covered, and to find the edge case the requirements forgot

• Comfort working without a playbook; you'll be proposing the tooling, not waiting for it

• Bachelor's degree in Computer Science, Geography or related fields, or the equivalent learned on the job

• Autonomy, curiosity, real eagerness to learn, and good energy

Benefits

• Competitive, results-based compensation

• Access to our employee stock options plan

• Private medical insurance

• Flexible work hours in a focused but casual environment

• Education Stipend

• Flexible compensation

• English classes

• A big vision: to help the world use location-based data to make better decisions. We believe that openness and sustainability are baked into this vision, and we’re sharing it with the world.

• Contribute to a platform used by top companies around the world. Your work will have a direct impact on our users and clients.

Originally posted on Himalayas