Quality Assurance Engineer III

About McDonalds:

One of the worlds largest employers with locations in more than 100 countries, McDonalds Corporation has corporate opportunities in Hyderabad. Our global offices serve as dynamic innovation and operations hubs, designed to expand McDonalds global talent base and in-house expertise. Our new office in Hyderabad will bring together knowledge across business, technology, analytics, and AI, accelerating our ability to deliver impactful solutions for the business and our customers across the globe.

One of the worlds largest employers with locations in more than 100 countries, McDonalds Corporation has corporate opportunities in Hyderabad. Our global offices serve as dynamic innovation and operations hubs, designed to expand McDonalds global talent base and in-house expertise. Our new office in Hyderabad will bring together knowledge across business, technology, analytics, and AI, accelerating our ability to deliver impactful solutions for the business and our customers across the globe.

Position Summary:

Quality Assurance Engineer III

Owns end-to-end quality engineering and technical support for PACE and the enterprise reporting and analytics applications built on it. Unlike a traditional manual QA role, this position is hands-on across the full stack: UI and API automation, SQL-based data testing of GCP pipelines, release validation, and production issue resolution, with AI and GenAI validation as those features are introduced. The role partners closely with full-stack developers, data engineers, product owners, business analysts, and global markets.

• Own the end-to-end test strategy, covering front-end applications, backend services, APIs, data pipelines, and AI-enabled features.
• Run functional, integration, regression, and end-to-end testing that follows each business workflow from source data to the user-facing report.
• Build and maintain UI automation with Playwright (TypeScript / JavaScript) and API and data tests with pytest, integrated into GitHub Actions as quality gates.
• Test batch and streaming pipelines on BigQuery, Dataflow, Pub/Sub, Confluent Kafka, Apache Airflow (Astronomer), and Talend, including backfills, re-runs, idempotency, and failure recovery.
• Validate data across raw, bronze, silver, and gold layers with SQL reconciliation, checking completeness, freshness, duplicates, referential integrity, and schema drift.
• Build dbt tests (generic, singular, unit, and contract), and automate data quality rules and a DQ scorecard with Dataplex Data Quality.
• Verify KPI calculations, business rules, aggregations, and filters in the web app, Tableau, and MicroStrategy reports against source data, including consistent satisfaction calculations across reporting surfaces.
• Assure Talend-to-dbt modernization and pipeline refactoring with parallel runs, row and hash checks, validation reports, and side-by-side output comparisons.
• As AI-powered features are introduced, test them on Vertex AI and Gemini, including retrieval data quality, bias, drift, prompt regression, and LLM / RAG output accuracy, grounding, and hallucination.
• Test performance, load, and security, including response times, BigQuery query cost, PAM-based role access and application role provisioning, row and column-level security, PII masking, and GDPR delete and notify flows across user groups and markets.
• Act as level-2 support behind the run-operations team, troubleshooting issues across UI, APIs, and data with Datadog, PagerDuty, and Cloud Monitoring and Logging, leading root cause analysis, and maintaining troubleshooting guides.
• Support the annual release cycle and new market onboarding through regression, deployment and post-release validation, configuration and access checks, localization and translation testing, and UAT.
• Use AI tools to generate test cases, test data, and automation scripts, and review every AI-generated test for correctness and coverage.

• 7–11 years of professional experience in software and data quality engineering, with 5+ years building test automation and 2+ years on GCP.
• Strong SQL, especially BigQuery, and Python (pytest, pandas).
• Hands-on UI and API automation with Playwright (TypeScript / JavaScript) and Postman.
• Hands-on dbt testing and orchestration with Apache Airflow (Astronomer).
• Good grasp of data modeling, medallion architecture, and warehouse concepts such as slowly changing dimensions, fact and dimension tables, and CDC.
• Experience with Dataplex data quality and dbt tests.
• Experience with CI/CD and Git, especially GitHub Actions.
• Shift-left mindset that automates first, defines clear quality gates, and explains data defects in terms of business impact.
• Responsible use of AI tools in testing, including keeping confidential and personal data out of prompts.
• Background in Computer Science, Engineering, or a related field with a bachelors degree or higher.
• Preferred: Java test automation (TestNG or JUnit 5, REST Assured); testing approaches for ML and GenAI models; LLM evaluation frameworks (Ragas, DeepEval, or Vertex AI Gen AI Evaluation); performance testing with JMeter or Gatling; Talend job validation; data governance, lineage (Dataplex), and privacy rules such as GDPR; GCP Professional Data Engineer or Professional ML Engineer certification; and retail or quick service restaurant data.
• Good to know: Selenium or Cypress; Great Expectations, Soda, or Monte Carlo; Vertex AI pipelines, Feature Store, or Model Monitoring; and BDD with Cucumber.

McDonalds is the worlds leading global foodservice retailer with over 40,000 locations in over 100 countries. Approximately 95% of McDonalds restaurants worldwide are owned and operated by independent local business owners. At McDonalds, we lead through our values centered on inclusivity, service, integrity, community, and family. Here is your chance to get in on something special as we grow our corporate team in India and allow you to grow your career.