QA Engineer

Location:

UKRole Type:
Permanent - Full Time

Job Location:

Hybrid Working - minimum of 2 days a week in our London office

Sagacity are the data intelligence people. Our proposition is businesses increase customer engagement and make moreinto the data businesses already have, and combine it with our data,insight, and action. Think of us asdata co-pilots for sales, marketing,ops, billing, credit and debt - clients typically see 5x returns within thefirst few months.

Founded in 2005, we are acustomer-centric business witha World Class +95 Net Promoter Score. We believe data should beat the heart of every company and while we are sector agnostic,primarily our clients are in thetelecoms & media, water, andnot for profit sectors.

We are a purpose led company and we believe that purpose comes before profit. We workas one team both with clients and internally, and are trusted todeliver quality in our standard sand in achieving successful client outcomes. We are open, honestand communicate in a jargon free, collaborative way, with all ourteams being agile and curious, and continuously learning to achieve our purpose. We believe that ifwe achieve our purpose then everything else will follow.

ABOUT SAGACITY

Clever with data... combining data,insight, and action to drive value

• Author, run, and maintain test plans across all phases of clientchecks, data quality rules, and migration parity — using SPHERE’s
• Investigate test failures systematically: trace root causes through the Databricks Lakehouse stack (bronze → silver → gold), distinguishpipeline bugs from data issues, and produce clear, evidenced findings for the development team
• Manage QA work items in Click Up throughout the delivery lifecycle —logging failures, tracking resolutions, promoting confirmed bugs, and closing issues when re-tests pass
• Collaborate with Data Engineers to agree expected behaviours, review data contracts, and validate fixes before they reach UAT or production
• Coordinate with UAT stakeholders to align acceptance criteria andshare QA findings in a way that non-technical audiences can act on
• Provide client-facing QA assurance — joining delivery meetingsto explain our testing approach, walk through results, and answer questions on QA methodology, coverage, and process
• Identify gaps and improvements in SPHERE — raise well-specifiedchange requests and feature requests; contribute to the platformcodebase where appetite and skill allow
• Keep QA coverage current as new views and data sources are
• onboarded — updating baselines, refreshing metadata, and extendingtest coverage without being asked
• Engage with AI agents for test authoring, investigation, resultanalysis, and documentation — working fluently in an AI-augmentedengineering environment.

• Client datasets are validated end-to-end before delivery, with nomaterial data quality escapes reaching UAT or production
• Test failures are investigated quickly, described clearly, and handedto developers with enough evidence that they can reproduce and fixwithout back-and-forth
• Click Up boards reflect the current state of QA — no stale or phantomissues, and Dev Issues are closed promptly when tests go green
• Clients and internal stakeholders feel well-informed and reassured aboutQA rigour, without needing to ask twice
• SPHERE improves over time because gaps in the platform are named,specified, and tracked — not just worked around
• QA coverage expands naturally with each deployment increment rather

you will own the quality assurance of Sagacity’s client data platform deployments — the Databricks Lakehouse pipelines, gold-layer views, and analytics datasets that drive marketing, billing, credit and debt outcomes for our clients across financial services, retail, energy, telecoms & media, water, and the not-for-profit sector. Working closely with our Data Engineers, Platform Engineer, UAT teams, and client stakeholders, you will design and execute structured test programmes using SPHERE (Sagacity’s internal QA platform), interpret results, triage failures, and provide confident assurance that the data leaving our platform is accurate, complete, and fit for purpose.

A typical…