PBT Group is seeking a highly skilled Senior Data Quality Automation Engineer / Data Test Analyst to join a strategic data initiative focused on ensuring the quality, reliability, and integrity of enterprise data within an Operational Data Store (ODS) environment.

This role has evolved beyond traditional testing and requires a strong blend of Quality Assurance, Automation Engineering, and Data Engineering capability. The successful candidate will focus on building scalable automated data quality frameworks, validating complex data pipelines, and embedding automated testing into modern data delivery processes.

This is an ideal opportunity for a senior specialist who enjoys solving complex data quality challenges, automating testing processes, and working within modern cloud and data engineering ecosystems.

Key Responsibilities

Data Quality & Validation

• Develop comprehensive test strategies and test plans for ODS data pipelines and models.
• Design and execute automated and manual test cases across bronze, silver, and gold data layers.
• Perform detailed data reconciliation between source systems and downstream platforms.
• Validate financial calculations, transformations, aggregations, and business rules.
• Analyse and troubleshoot complex data quality issues across large datasets.

Automation Engineering

• Design, build, and maintain reusable automated testing frameworks for backend and data validation.
• Automate ETL/ELT validation processes and regression testing.
• Create automated SQL-based validation scripts and reconciliation checks.
• Implement schema validation, data type checks, completeness testing, and consistency validation.
• Integrate automated data quality checks into CI/CD pipelines.

Data & Platform Testing

• Perform end-to-end testing of data pipelines and transformations.
• Work with dbt testing frameworks including unit, integration, and data tests.
• Conduct performance and scalability testing for high-volume data environments.
• Collaborate closely with Data Engineers, Architects, Analysts, and Business stakeholders.

Governance & Quality Assurance

• Log, track, and manage defects through to resolution.
• Ensure adherence to data governance and quality standards.
• Contribute to best practices for data quality engineering and test automation.

Required Skills & Experience

Essential

• 5+ years’ experience in Data Testing, QA Automation, or Data Engineering environments.
• Strong SQL expertise with experience writing complex validation and reconciliation queries.
• Solid Python scripting and automation experience.
• Experience testing ETL/ELT pipelines and large-scale data platforms.
• Hands-on experience with automated data quality testing frameworks.
• Strong understanding of data warehousing concepts and layered architectures (bronze/silver/gold).
• Experience working with dbt testing frameworks.
• Exposure to CI/CD tools such as Jenkins, GitLab, or Azure DevOps.
• Strong analytical and problem-solving capability.
• Excellent attention to detail.

Advantageous

• Experience within financial services, banking, or regulated environments.
• Exposure to big data technologies such as Spark or Hive.
• Experience with cloud data platforms.
• Familiarity with modern data engineering practices and DevOps principles.

Ideal Candidate Profile

We are looking for a senior-level consultant who:

• Thinks like an engineer and a tester.
• Can build scalable automation frameworks rather than rely on manual validation.
• Understands both data engineering and quality assurance principles.
• Is comfortable engaging with technical and business stakeholders.
• Can work independently while contributing to broader delivery teams.

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