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Test Engineer (Automation )

Sabenza IT & Recruitment

Job Location:

Cape Town - South Africa

Monthly Salary: Not provided by the employer

Experience Required: 5years

Posted: 23 September 2026 (4 hours ago)

Application Deadline: 21 December 2026

Vacancies: 1 Vacancy

Job Summary

We are looking for an experienced Test Automation Engineer / Automation Tester to play a critical role in enabling quality at speed.

You will design and implement both manual and automated test scenarios across the Software Development Life Cycle (SDLC) with a focus on delivering clean secure and reliable software.

This is a dynamic high-energy environment where change is constant quality is paramount and collaboration is key. You will work within a team that values adaptability problem-solving and ownership while contributing to the successful delivery of technology solutions.

Requirements

Key Responsibilities

Design develop and maintain automated test frameworks and scripts.
Execute automated and manual testing across the SDLC.
Develop comprehensive test scenarios and test cases.
Perform integration regression and functional testing.
Identify document and troubleshoot defects.
Support API performance and security testing activities.
Integrate automated testing into CI/CD pipelines.
Collaborate with developers analysts and other technology stakeholders.
Contribute to continuous improvement of testing processes tools and methodologies.
Ensure software releases meet defined quality and reliability standards.

Key Requirements:

A completed qualification in Software Testing (ISTQB Foundation preferred).
35 years experience in automation testing including framework design scripting and execution.
Proficiency with tools such as Playwright Selenium BrowserStack and Postman.
Experience with CI/CD tools such as Jenkins or GitLab.
Solid understanding of the full SDLC integration testing regression testing and test case design.
Exposure to API performance and/or security testing.
Experience working with Agile methodologies including Scrum or Kanban.
Exposure to cloud platforms such as AWS or Azure
Strong attention to detail problem-solving ability and a .quality-first mindset.
A collaborative approach and the ability to thrive in a fast-paced continuously changing environment.

Required Skills:

Key Responsibilities Conduct advanced data analysis across multiple business areas to identify trends patterns opportunities and potential data issues. Translate complex analytical findings into clear business insights and recommendations for technical and non-technical stakeholders. Lead data analysis projects taking ownership of planning scoping timelines delivery and quality. Develop and maintain KPIs reports forecasting scenario analysis and dashboards to support informed decision-making. Apply advanced statistical techniques and develop simple predictive models following appropriate data science and analytical lifecycles. Work closely with business and technical teams to understand requirements data flows processes and downstream data needs. Act as a bridge between business stakeholders data analysts engineers and data scientists. Challenge assumptions vague requirements and requests that may not address the underlying business need. Identify opportunities to improve processes data assets and analytical ways of working. Ensure data analysis is accurate well documented repeatable and suitable for implementation with minimal rework. Support data modelling and data mart development ensuring data can be effectively used across multiple teams. Identify and address data quality gaps and proactively challenge solution designs to ensure appropriate data requirements are considered. Apply GenAI AI and modern analytical tooling where appropriate to improve productivity and analytical outcomes. Mentor guide and upskill less experienced analysts in areas such as SQL Python data visualisation and analytical standards. Participate in knowledge-sharing initiatives code reviews interviews and subject matter guidance. Build strong relationships with stakeholders and manage expectations requirements and potential conflicts effectively. Key Technical Requirements Significant experience in Data Analysis preferably within banking or financial services. Advanced proficiency in SQL including complex queries query optimisation and working with large datasets. Strong Python or R skills including data manipulation and visualisation libraries such as pandas NumPy Matplotlib or Seaborn. Advanced Excel including macros and VBA. Strong Power BI Tableau or similar data visualisation and dashboarding experience. Advanced statistical analysis and modelling. Experience with predictive analytics and its application to business/financial data. Knowledge of data modelling techniques and data structures. Experience with data quality validation and analytical controls. Understanding of risk analysis and its application within financial services. Knowledge of financial products services industry trends regulations and compliance considerations. Exposure to AI/GenAI and modern data/analytical tools would be advantageous.

Required Education:

Experience & Qualifications Proven experience delivering complex data analysis projects and demonstrating business impact through data-driven insights. Significant experience in data analysis with financial services/banking experience strongly preferred. Bachelors or Honours Degree in Data Analytical Technical or a related field.

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