Solutions QA Engineers
Posted Today by 1765948816
Negotiable
Outside
Remote
USA
Summary: The Solutions QA Engineer role focuses on exploring, testing, and documenting failure modes across various workflows using modern data stack tools. This position emphasizes manual testing to identify problem areas that may later be automated. The engineer will work independently within a fully remote team, collaborating with support and product teams to enhance integration quality. Strong communication and documentation skills are essential for success in this role.
Key Responsibilities:
- Execute exploratory, production-oriented QA on customer-critical integration paths across tools like DBT, Airflow, Terraform, ADF, and GitHub Actions
- Recreate and document integration issues surfaced by customers and support
- Test and validate APIs, CLI, and system behavior under different configurations
- Partner with Support and Product to prioritize edge case testing aligned with real-world impact
- Identify and articulate blast radius and system behavior under unexpected or invalid configurations
- File actionable, reproduction-ready bugs with context for engineering
- Track coverage across tested tools, connectors, and orchestration flows
- Contribute to early-stage runbooks and automation plans, once common patterns are identified
- Serve as an internal integration hunter to expose gaps before customers do
Key Skills:
- Experience in software QA, support engineering, or technical testing roles
- Familiarity with modern data engineering platforms and orchestrators
- Ability to manually set up test environments and reproduce issues across multiple systems
- Experience with APIs, CLI tools, and validating system integrations
- Strong written skills for defect reproduction, test case documentation, and QA communication
- Self-starter mindset able to explore unfamiliar systems, dig for failure paths, and propose next steps
- Ability to work independently in a fully remote team
- Comfortable testing in complex, high-variance customer environments (non-standard configurations)
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Job Overview:
Explore, test, and document failure modes across API, CLI, and orchestration workflows using modern data stack tools (Snowflake, Databricks, Airflow, Fivetran, Terraform, DBT, Azure Data Factory, AWS, GitHub Actions etc.). This is a manual-first role to discover the problem space automation may follow as patterns emerge.
Required:
- Experience in software QA, support engineering, or technical testing roles
- Familiarity with modern data engineering platforms and orchestrators:
- Examples: Airflow, Terraform, DBT, Databricks, GitHub Actions, Azure Data Factory
- Ability to manually set up test environments and reproduce issues across multiple systems
- Experience with APIs, CLI tools, and validating system integrations
- Strong written skills for defect reproduction, test case documentation, and QA communication
- Self-starter mindset able to explore unfamiliar systems, dig for failure paths, and propose next steps
- Ability to work independently in a fully remote team
- Comfortable testing in complex, high-variance customer environments (non-standard configurations)
Job Description:
- Execute exploratory, production-oriented QA on customer-critical integration paths across tools like DBT, Airflow, Terraform, ADF, and GitHub Actions
- Recreate and document integration issues surfaced by customers and support
- Test and validate APIs, CLI, and system behavior under different configurations
- Partner with Support and Product to prioritize edge case testing aligned with real-world impact
- Identify and articulate blast radius and system behavior under unexpected or invalid configurations
- File actionable, reproduction-ready bugs with context for engineering
- Track coverage across tested tools, connectors, and orchestration flows
- Contribute to early-stage runbooks and automation plans, once common patterns are identified
- Serve as an internal integration hunter to expose gaps before customers do