Avenga logo

Senior Automation QA Engineer

Avenga

onsitefull-time
Posted Oct 7, 2026

**Role & seniority: ** Principal Automation Quality Engineer (QA)

**Stack/tools: ** SQL; Python (data validation + test automation); test automation frameworks/infrastructure; data quality checks (schema validation, source-to-target reconciliation); Agile/SDLC practices; AI coding/testing tools (practical experience)

**Top 3 responsibilities: **

  • Define/ensure requirements are testable; design and execute manual + automated test plans for ETL/pipelines

  • Validate data end-to-end (schema checks, data validation, reconciliation, staging/release validation)

  • Own QA across the lifecycle: defect tracking/resolution, QA reporting, and process/automation improvements

  • Must-have skills:

    • Strong SQL; experience testing data pipelines/ETL and transformations/outputs

    • Python for test automation and data validation

    • Knowledge of data quality checks: schema validation + source-to-target reconciliation

    • Test automation experience; analytical/root-cause analysis; Agile/SDLC understanding

    • English communication; defect lifecycle management

  • Nice-to-haves:

    • Practical experience with AI coding/testing tools
  • Location & work type: Not specified in provided text (international firm; remote/hybrid/on-site not mentioned).

Full Description

Avenga is an international engineering firm helping businesses operate with AI at the core. With 6,000+ experts worldwide, we combine engineering expertise with AI-native thinking to turn ambitious ideas into real-world impact across industries, technologies, and markets. About the Role We are looking for a Principal Automation Quality Engineer to ensure the quality, reliability, and accuracy of data pipelines and ETL processes. You will work closely with Data Engineers and Product Owners, combining strong SQL skills, test automation, and data validation techniques. Key Responsibilities Review requirements and ensure they are testable. Create and execute manual and automated test plans. Test ETL processes, data pipelines, transformations, and outputs. Perform data validation, schema checks, and source-to-target reconciliation. Conduct end-to-end testing of new features and pipeline changes. Perform staging and release validation. Own QA activities throughout the development lifecycle. Identify, report, and track defects through resolution. Analyze test results and prepare QA reports. Identify opportunities to improve QA processes and automation. Collaborate closely with Product Owners and Data Engineers. Requirements 3–5 + years of QA experience, preferably in data engineering or ETL testing. Strong SQL skills. Working knowledge of Python for data validation and test automation. Experience testing data pipelines and ETL processes. Knowledge of data quality checks, schema validation, and source-to-target reconciliation. Experience with test automation and automation infrastructure. Strong understanding of Agile, SDLC, and defect lifecycle. Strong analytical and root-cause analysis skills. Excellent English communication skills. Practical experience using AI coding/testing tools. People are at the core of Avenga. We provide equal opportunities regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to a respectful environment where everyone can be themselves, share their ideas, and feel that they belong.

SQLPythonETL testingData validationTest automationData pipelinesSchema validationSource-to-target reconciliationAgileSDLCDefect lifecycleRoot-cause analysisAI coding toolsData quality checks

Cookies & analytics consent

We serve candidates globally, so we only activate Google Tag Manager and other analytics after you opt in. This keeps us aligned with GDPR/UK DPA, ePrivacy, LGPD, and similar rules. Essential features still run without analytics cookies.

Read how we use data in our Privacy Policy and Terms of Service.