Assignment Description
Conduct an analysis and develop a roadmap for improving the testing approach within the ART Analysis & Insight (ANI). ANI is an ART where both software applications and data applications are developed and maintained.

Scope and Activities:
- Analysis Phase.
- Perform an analysis of five teams regarding their current testing approach:
o Team level: test strategy, test automation, quality assurance.
o Integration and chain level: end-to-end testing, dependencies, and risks.
- Take into account the capabilities of the existing data engineering platform and the combination of software and data applications.
- Validate the current shift-left approach in two teams that are delivering new data products.
- Develop a roadmap with improvement points for test processes, test automation, and quality assurance.

After the Analysis phase an explicit Go / No go decision for further implementation will be made together with RTE, SA and PM.

Implementation Phase
- Define and communicate improvements to teams and stakeholders.
- Create buy-in with Product Management, in collaboration with the System Architect and Release Train Engineer (RTE).
- Implement improvements using the "I do, We do, You do" methodology:
o I do: demonstrate best practices.
o We do: guide teams in applying them.
o You do: enable teams to execute independently.
- Contribute to the realization of improved test processes and automation at both team and chain level.

Next to that, the assignment includes the validation of the test approach of two teams creating new data products en define improvements.
The assignment will take place within the framework of the Enexis Test Strategy and in close collaboration with the Quality For Excellence team at Enexis Digital.

As a QA & Test Lead Engineer with a strong affinity for both software engineering and data engineering, you will be responsible for increasing test maturity within complex software and data environments within the ART ANI (Asset Net capacity & Insight). You play a key role in establishing robust test strategies and implementing test automation for software and data pipelines.
You work closely with multidisciplinary DevOps teams to achieve built-in quality and shift-left testing. You coach engineers in applying best practices for requirement management, risk-based testing, test automation, and quality gates in CI/CD pipelines.

Key Responsibilities:
- Design and implement end-to-end quality and test strategies for software and data;§ Set up and improve test automation;
- Configure quality gates within CI/CD;
- Advise on risks and quality assurance in data integration projects;
- Monitor and report on test results, including data quality and performance metrics;
- Coach teams on test automation and testing best practices.

The ideal candidate is a test engineer capable of defining a test strategy across multiple teams and guiding them through a "do it yourself, do it together, delegate" approach.

Experience and Skills:
- At least 5 years of experience in agile software development, quality engineering, and test automation.
- Experience with data engineering concepts and tools (ETL, data pipelines, data governance).
- Hands-on experience with CI/CD and test automation in a data engineering context.
- Knowledge of frameworks such as SAFe, Scrum, DevOps, and testing concepts (TDD, BDD, risk-based testing).
- Experience with test tools and data engineering platforms such as Matillion (preferred), Azure Data Factory, dbt, Snowflake, SAP S/4HANA.
- Experience with hybrid cloud architectures and SaaS integrations.
- Strong communication skills and coaching experience