Job Description

Role: QA Engineer

Location: Remote

Must have experience with Azure, databricks and snowflake

Our client is hiring contract Solutions QA Engineers to help harden the production
experience of our Slingshot platform-a modern data optimization product used by large
enterprise data teams. This role is not traditional QA. You'll be hunting real-world customer
failures that slip through happy-path test coverage, especially those stemming from 3rd-party
integration edge cases.
You'll work directly with product, engineering, and support to identify bugs that impact reliability
and customer trust. Your focus: 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.



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
Required Qualifications
3+ years 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)
Nice to Have (Not Required)
Prior experience in Support Engineering, SRE, or Solutions QA roles
Familiarity with AWS, Snowflake, Databricks, or enterprise data warehouse
environments
Scripting or automation skills (e.g. Python, Bash, Postman collections, etc.)
Exposure to data quality tools or ETL pipeline validation
Background in high-scale enterprise B2B SaaS environments

Job Tags

Contract work, Remote work,

Similar Jobs