QE Automation Lead

Salary: £55,000 - 95,000 per year

Requirements:

• We need extensive experience in data engineering and test management.
• We need strong technical capability in Python or PySpark, SQL, Oracle, HDFS, and YAML.
• We need experience leading test automation in data testing, ideally within large-scale transformation programmes.
• We need proven experience operating as a highly technical Test Lead or Automation Lead for QE teams, including test data and test environment management.
• We need hands-on experience architecting, designing, and implementing scalable automated data testing frameworks, including reconciliation and validation logic.
• We need knowledge of AI-driven testing solutions and automation accelerators to improve test efficiency and software quality.
• We need a deep understanding of AWS data pipelines, AWS Glue, Data Warehouse, Data Lakehouse, ETL/ELT processes, data quality concepts, data infrastructure, and related testing methodologies.
• We need experience building advanced test automation frameworks from scratch using object-oriented and scripted languages.
• We need breadth across at least two of the following technologies: JavaScript/TypeScript, Java, C#, or Python.
• We need a strong understanding of object-oriented programming principles and practical application of those principles.
• We need experience writing test plans for functional and non-functional testing in a data environment with a focus on data quality.
• We need strong problem-solving skills and the ability to think critically.
• We need excellent communication skills to explain complex technical concepts to both technical and non-technical stakeholders.
• We need experience with test coverage, defect management, and reporting tools such as JIRA, XRAY, and ADO.
• BPSS is required, and SC is not mandated but may be strongly likely to be required.

Responsibilities:

• We will act as the Test Lead for automated data testing, accountable for planning, execution, and reporting of automation activities.
• We will lead and manage a team of Test Engineers and SDETs, providing day-to-day direction, technical guidance, and coaching.
• We will own automation scope, backlog, and priorities in line with programme plans and milestones.
• We will ensure testing activity aligns with the overall Test Strategy and governance set by the QAT Lead.
• We will monitor progress to ensure the Test Approach is applied with sufficient auditable test coverage and results across Unit, System, Automated Interface/E2E, Performance, Operational Acceptance, and UAT data validation.
• We will support testing quality audits.
• We will design and implement an automated test approach aligned to a Data Factory testing model and leveraging AI augmentation.
• We will define and maintain automation test frameworks, standards, and patterns for data testing.
• We will ensure automation provides sufficient risk-based test coverage and repeatable, auditable results.
• We will remain hands-on by supporting execution, including automated test scripts and AI utilities, validation logic and data queries, and test framework tooling.
• We will lead testing of AWS-based Lakehouse and data pipeline solutions, including AWS Glue, Apache Iceberg, AI-enabled ETL accelerators, Neo4j, Python/PySpark, SQL, and YAML-driven configurations.
• We will ensure quality issues, risks, and data defects are identified early, clearly documented, and effectively triaged.
• We will monitor, track, and report test progress across multiple factory teams through meaningful reports and dashboards.
• We will analyse defect trends and test results to identify systemic quality risks.
• We will provide input to test exit decisions and go-live readiness assessments.
• We will support formal Test Exit Reports and quality assurance reviews for quality gates, entry and exit criteria, test coverage expectations, and acceptance thresholds.
• We will work closely with scrum team members, data engineers, platform engineers, product owners, business SMEs, and third-party partners to ensure connected technical testing solutions.
• We will translate technical test outcomes into clear insights for the QE Lead.
• We will act as a technical quality authority within scrum and delivery teams.
• We will ensure effective use of test case and defect management tooling such as ADO, JIRA, and XRAY.
• We will integrate automated tests into CI/CD pipelines such as GitHub Actions or similar.
• We will support and guide test data management, including synthetic data creation, masking, and environment readiness.

Technologies:

• AI
• AWS
• AWS Glue
• C#
• CI/CD
• Data Warehouse
• E2E
• ETL
• GitHub
• Support
• JIRA
• Java
• JavaScript
• Neo4J
• Oracle
• Python
• PySpark
• SQL
• TypeScript
• Cloud
• API
• DevOps
• Network
• OOP

More:

We are NTT DATA, a global business and technology services, AI, and digital infrastructure leader with over $30 billion in revenue. We co-innovate solutions with clients and partners worldwide and serve 75% of the Fortune Global 100. Our teams span more than 70 countries, and we encourage experimentation, recognise great work, and invest heavily in R&D as part of NTT Group. We offer tailored benefits that support physical, emotional, and financial wellbeing, continuous learning and development opportunities, and flexible work options. We are proud to be a Global Top Employer and are committed to equity, diversity, inclusion, and fair employment practices across our workforce.

last updated 35 week of 2026