Inhuurbron

IT Software Quality Engineering

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IT Software Quality Engineer (ETL/Big Data testing, SQL, Azure) voor Shell, 40u/week, Rotterdam, start 14-08-2026.

Locatie
Rotterdam
Werkvorm
op locatie
Uren
40 uur per week
Contractvorm
detachering
Startdatum
Looptijd
11 maanden (tot 30 juli 2027)
Sluitingsdatum
Eerste waarneming
Opdrachtgever
Shell

Eisen

Wensen

Omschrijving

IT Software Quality Engineering. Work Details: Experience: around 14 Years. Employment Type: Contractual. Work Location: Netherlands. Role Overview: We are looking for an experienced IT Software Quality Engineer to drive quality assurance activities across complex data platforms and cloud-based ecosystems. The role requires strong expertise in ETL and Big Data testing, data validation, SQL, and test automation. The successful candidate will be responsible for ensuring data accuracy, integrity, and reliability across end-to-end data pipelines while collaborating with cross-functional teams to deliver high-quality solutions. Key Responsibilities: ETL & Data Validation: Perform end-to-end testing of ETL and Data workflows. Validate data extraction, transformation, and loading processes. Conduct data reconciliation and cross-system validation activities. Ensure data quality, completeness, consistency, and accuracy across source and target systems. Test Planning & Execution: Analyze business requirements and create detailed test scenarios and test cases. Develop comprehensive test strategies aligned with business and technical requirements. Execute functional, integration, system and regression testing. Ensure adequate test coverage and quality across releases. SQL & Data Analysis: Perform advanced SQL-based data validation and analysis. Validate complex data transformations, aggregations, joins, and business rules. Investigate and troubleshoot data-related defects and inconsistencies. Automation & Tools (good to have): Develop and maintain automated data validation frameworks using Python, PySpark, and Pandas. Create reusable automation utilities to improve testing efficiency. Support continuous improvement of test automation capabilities. Cloud & Data Platform Testing: Validate data pipelines built on Azure Data Factory (ADF). Test data processing and storage solutions on Azure Databricks and Azure Data Lake. Ensure seamless integration between cloud-based data services. API & Integration Testing: Validate data exchange across integrated applications and services. Perform API testing using tools such as Postman. Defect Management: Manage the complete defect lifecycle from identification through closure. Collaborate closely with development and integration teams to resolve issues effectively. Reporting & Stakeholder Communication: Track and report testing progress, quality metrics, risks, dependencies, and blockers. Provide regular status updates to project stakeholders. Work closely with developers, business analysts, product owners, and business users to ensure successful delivery. Quality & Risk Management: Identify quality risks proactively and drive mitigation plans. Ensure compliance with organizational QA standards, processes, and governance practices. Required Skills & Experience: Must-Have Skills: ETL Testing / Big Data Testing, Manual Testing, BI / Reporting Validation, Advanced SQL, Data Validation and Reconciliation, End-to-End Test Lifecycle Management, Azure DevOps, ETL Frameworks and Processes. Hands-On Experience: Python, PySpark, Pandas, Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Gen2, Postman. Educational Qualification: Bachelor's or Master's Degree in Computer Science, Information Technology, Data Engineering, or Related Technical Discipline. Key Competencies: Strong analytical and problem-solving skills, Attention to detail and quality focus, Ownership and accountability, Effective stakeholder management, Excellent verbal and written communication skills, Proactive risk identification and mitigation. Preferred Candidate Profile: Strong experience in data-centric testing environments. Exposure to cloud-based data platforms and modern data architectures. Ability to independently lead testing activities and coordinate with stakeholders. Interest in emerging AI-driven testing approaches and intellige.

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