Principal Quality Engineer- Dallas, TX

Photon•Dallas, TX

1d•$37,000 - $131,000•Onsite

About The Position

Our team is looking for a Principal Automation Engineer to accelerate quality engineering practices across data and API-centric initiatives. This role embeds with a delivery team to drive process enablement, automation maturity, and modernization of data and reporting platforms. The engineer will design, build, and maintain robust automation frameworks that validate APIs, data pipelines, and reporting outputs — while coaching teams on modern QE practices and leveraging AI-assisted development tools to accelerate delivery.

Requirements

10+ years of professional experience in software quality engineering, test automation, or SDET roles.
Significant hands-on experience in API Test Automation: Design, develop, and maintain API automation suites using Cucumber, Serenity BDD, and/or Karate frameworks.
Experience building and executing automated data validation strategies across pipelines, warehouses, and reporting layers (source-to-target, schema, integrity, reconciliation, lineage).
Experience validating reporting and BI tools by comparing report outputs against source databases using complex and optimized queries.
Demonstrated experience with performance testing using Rush Hour or comparable tools (e.g., JMeter, Gatling, k6) with willingness/ability to use Rush Hour.
Understanding of architecting reusable, scalable test automation frameworks with a strong proficiency in Java, with supporting tooling/scripts in Python as needed.
Expertise in authoring advanced SQL queries to validate data correctness across heterogeneous data stores.
Awareness of integrating automated test suites into CI/CD pipelines; ensuring fast feedback loops and reliable, deterministic test execution.
Experience with version control (Git) and modern collaborative development workflows.
Hands-on experience with AI code-assist tools (e.g., GitHub Copilot, Copilot Chat, or similar) integrated into a daily development workflow.
Experience with contract testing (e.g., Pact) and/or API specification tooling (OpenAPI/Swagger).
Experience testing modern data platforms (e.g., Snowflake, Databricks, BigQuery) and/or reporting platforms (e.g., Tableau, Power BI, MicroStrategy).
Experience with containerization (Docker) and cloud platforms (AWS, Azure, or GCP).
Familiarity with observability tooling for test diagnostics (logs, traces, metrics).
Advanced SQL skills for data validation and analysis across relational data sources.
Proven experience designing and executing data validation strategies (ETL/ELT testing, source-to-target, reconciliation, schema validation).
Awareness of REST API design, contracts, and testing patterns (including authentication, schema/contract validation, negative testing).
Excellent communication skills with the ability to enable and coach delivery squads.

Nice To Haves

Background in financial services or other regulated/data-intensive domains.

Responsibilities

Design, build, and maintain robust automation frameworks that validate APIs, data pipelines, and reporting outputs.
Coach teams on modern QE practices.
Leverage AI-assisted development tools to accelerate delivery.
Design and execute data validation strategies (ETL/ELT testing, source-to-target, reconciliation, schema validation).
Mature QE practices within squads, including shift-left testing, contract testing, test data management, and quality gating.
Contribute to the modernization of data and reporting platforms by establishing automated quality checks that de-risk migration and refactoring efforts.
Enable and coach delivery squads.
Lead or coach agile QE and audit practices within squads.
Work cross-functionally with developers, data engineers, product owners, and other QE practitioners.
Mentor team members on automation best practices.
Produce clear, actionable quality metrics and dashboards that inform delivery decisions.