Role & seniority: QA Engineer (government context; likely mid-senior level)

Stack/tools: AWS, Databricks, data quality tooling, Rest Assured, QA frameworks, Gherkin, SQL, Python; end-to-end automated integration tests

Top 3 responsibilities

Develop and implement QA processes for accurate and secure data migration from Legacy to AWS; validate transformation logic in Databricks
Perform end-to-end testing of analytical workflows and dashboards; review and validate analytical models and outputs
Communicate test results to technical and non-technical stakeholders; mentor/coach others; drive improvements and investigate process opportunities

Must-have skills

Government experience and clearance mindset (BPSS)
Strong data quality principles; AWS and Databricks familiarity
QA expertise with automated testing tools, Rest Assured, QA frameworks, Gherkin
SQL proficiency for complex data validation; Python scripting

Nice-to-haves

Ability to coach/mentor team members; lead investigative work; train others on techniques and frameworks
Strong communication of non-functional test results; critical thinking and problem-solving across teams
Location & work type: Remote; 12-month contract; Inside IR35; government-domain project requirements

Notes: Includes required focus on data migration validation, transformation logic, and end-to-end analytics testing; emphasizes collaboration, coaching, and stakeholder communication.

Full Description

Job Title: QA

Rate: £550 (Inside IR35)

Duration: 12 Months

Location: Remote

Clearance: BPSS

Stages: 1 Stage Must Have Government Experience

design and execute a wide range of testing techniques and communicate test results to both technical and non-technical stakeholders make decisions on the environment for testing, and can coach others identify defects, alert the business to them, and help to prioritise them based on defect severity design and execute a wide range of non-functional testing techniques communicate non-functional test results to both technical and non-technical stakeholders make decisions on running types of non-functional testing coach and mentor others identify defects, alert the business to them, and help to prioritise them based on defect severity demonstrate a good working knowledge of different tools and techniques, and can train others advise others on testing techniques and frameworks effectively research, plan and train others within the team think creatively, ask the right questions and critically evaluate and communicate findings to a larger team lead investigative work into problems and opportunities in existing processes drive the collection of information and the creation of recommendations for improvements absorb large amounts of conflicting information and use it to determine solutions

Key Responsibilities and Technical Skills

Develop and implement QA processes and procedures to ensure accurate and secure data migration from the Legacy system to AWS.
Validate the transformation logic applied during data processing in Databricks.
Review and validate analytical models and outputs produced by the analytical team.
Perform end-to-end testing of analytical workflows and dashboards.

Technical Skills

Strong understanding of data quality principles and best practices.
Familiarity with AWS services and Databricks.
Proficiency in QA tools, technologies and e2e automated integration tests (eg, automated testing tools- Rest Assured, QA frameworks, Gherkin).
Ability to write and execute complex SQL queries for data validation.
Familiarity with Scripting languages such as Python