QA Engineer

Stichting Codam; Greater London; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Sagacity seeks a QA Engineer focusing on data quality and testing for client data platform deployments in a fast-moving AI-enabled environment. You will design, run, and govern structured test programs across Databricks pipelines and analytics datasets, ensuring accuracy, completeness, and fit for purpose.

You will work with AI-assisted tooling, collaborate with Data Engineers, UAT teams, and client stakeholders, and travel across the UK as needed.

Qualifications

• Strong SQL skills and complex analytical queries to interrogate data
• Hands-on Databricks experience and Spark SQL understanding
• Familiarity with PySpark or Spark SQL and data transformations
• Knowledge of Lakehouse/medallion architecture and data flow across layers
• Familiarity with YAML-based configuration and programmatic test definitions
• Experience with Git and basic engineering practices
• Interest in AI-assisted workflows and AI tooling for testing

Responsibilities

• Author, run, and maintain test plans across client data checks and data quality rules
• Investigate test failures by tracing root causes in the Databricks Lakehouse stack
• Manage QA work items in ClickUp during delivery lifecycle
• Collaborate with Data Engineers to validate fixes before UAT or production
• Coordinate with UAT stakeholders to align acceptance criteria and QA findings
• Provide client-facing QA assurance during delivery meetings
• Identify gaps and raise change requests to SPHERE as needed
• Keep QA coverage current with evolving data sources
• Engage with AI agents for test authoring and analysis

Skills

SQL

Databricks

PySpark

Lakehouse

YAML

Git

AI-assisted workflows

Tools

Databricks

PySpark

Spark SQL

Unity Catalog

YAML

Job description

Location: UKRole Type: Permanent - Full TimeJob Location: Hybrid Working - minimum of 2 days a week in our London office

Sagacity are the data intelligencepeople. Our proposition isbusinesses increase customerengagement and make moreinto the data businesses alreadyhave, and combine it with our data,insight, and action. Think of us asdata co-pilots for sales, marketing,ops, billing, credit and debt - clientstypically see 5x returns within thefirst few months.

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

We are a purpose led companyand we believe that purposecomes before profit. We workas one team both with clientsand internally, and are trusted todeliver quality in our standardsand in achieving successful clientoutcomes. We are open, honestand communicate in a jargonfree, collaborative way, with all ourteams being agile and curious, andcontinuously learning to achieveour purpose. We believe that ifwe achieve our purpose theneverything else will follow.

ABOUT SAGACITY

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

Key Responsibilities

• 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 theDatabricks Lakehouse stack (bronze → silver → gold), distinguishpipeline bugs from data issues, and produce clear, evidenced findingsfor the development team
• Manage QA work items in ClickUp throughout the delivery lifecycle —logging failures, tracking resolutions, promoting confirmed bugs, andclosing issues when re-tests pass
• Collaborate with Data Engineers to agree expected behaviours, reviewdata 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 answerquestions 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.

What Sucess Looks Like in the Role

• 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
• ClickUp 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

Role Overview

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 day will see you working alongside AI agents for authoring tests, analysing results, and managing work items — treating AI-assisted tooling as a first-class part of your workflow rather than a novelty.

Technical

• Strong SQL skills — comfortable writing and reading complex analytical queries (window functions, CTEs, aggregations) to interrogate data andverify correctness
• Hands-on experience with Databricks — running queries, navigatingUnity Catalog, reading Spark job outputs and understanding what they
• Working knowledge of PySpark or Spark SQL — enough to read pipelinecode, understand transformations, and trace where data
• Understanding of Lakehouse / medallion architecture (bronze-silvergold) and how data flows and changes shape across layers
• Familiarity with YAML-based configuration and a willingness to authorstructured test definitions programmatically
• Comfort with Git and basic engineering practices — branching, committing, reading diffs, and understanding what changed between pipeline versions
• Experience with or appetite for AI-assisted workflows — working withlarge language model agents as a genuine productivity tool, not just for

Experience

• 3–5+ years in a data quality, data testing, analytics engineering, or data engineering role with a strong quality focus
• Demonstrable experience investigating data issues in a complex, mul ti-source environment and communicating findings clearly
• Exposure to structured test frameworks, data observability tooling, or formal QA methodology in a data context
• Experience working directly with development teams in an agile or iterative delivery environment
• Client-facing or stakeholder-facing experience — comfortable presenting technical findings to non-technical audiences

Behaviours

• Detail-oriented by nature — you notice when numbers don’t add up and you follow the thread until you understand why
• Solutions-oriented and self-directed — you don’t wait to be told what to test next; you look at the data and ask the right questions
• Clear communicator, written and verbal — able to translate a complex data discrepancy into a finding a developer can act on and a client can
• Positive and collaborative — a team player who shares knowledge,supports peers, and improves the process, not just the output
• Comfortable under pressure and adaptable when priorities shift midsprint
• Curious about the platform you work on — you notice friction, describe it precisely, and push for improvements
• Self-motivated with strong organisational skills — able to managemultiple client streams in parallel without dropping threads
• Able to travel throughout the UK
• Have the right to work in the UK
• Committed to personal development — especially in the fast-moving space of AI-assisted engineering

If you would like to join a unique working environment, with a sociableculture, where work is done a little bit differently – and we believe‘better’ - then we look forward to hearing from you!

We achieve this through ourcore values:

One Team

Quality Delivery

Agile & Curious

Open, Honest, Simple Communication

Success in any business isultimately about its people; theirdedication and enthusiasm.

We recognise the value of ourpeople and their commitmentto working together to achievesuccessful outcomes.

At Sagacity, we:

• believe working with our clients
• coach and mentor our clients’ teamsso our data and solutions live on
• believe in delivering benefits as we

ABOUT SAGACITY

People at Sagacity