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Data Quality Advisor, Professional Services Analytics
<p><strong>Location:</strong> United Kingdom<br /> <strong>Remote:</strong> Yes<br /> <strong>Job Type:</strong> Permanent<br /> <strong>Salary:</strong> Negotiable</p> <p>You will join a professional services environment that delivers data quality and governance remediation for multi-team clients under defined controls and timelines. The work is practical: establish what “correct” means for priority measures, put repeatable checks in place, and leave behind operating patterns that internal teams can sustain. The role is fully remote within the UK, with planned workshops when they materially improve decision-making.</p> <p><strong>Organisation</strong><br /> Assignments typically involve regulated or high-scrutiny reporting where disputes are caused by definition drift, inconsistent cut-offs and undocumented backfills. You will be expected to work with data owners, platform engineers, analysts and security leads, and to keep discussions grounded in evidence rather than opinion. Delivery is usually run in two-week cycles with a weekly steering checkpoint to unblock decisions and confirm scope boundaries.</p> <ul> <li>Typical delivery is on cloud platforms with a governed warehouse or lakehouse.</li> <li>You will work with AWS Glue Data Catalog for ownership and classification, query curated layers through Athena or a warehouse, and build curated tables on Iceberg or equivalent open table formats.</li> <li>Orchestration is often handled with Dagster or managed schedulers, with change control through GitHub pull requests and Terraform-managed environments.</li> <li>Where lineage is required, you will use OpenLineage-compatible metadata so impact on downstream packs is visible before a change is promoted.</li> </ul> <p><strong>Key responsibilities</strong></p> <ul> <li>Mapping the critical measures to their source systems, identifying where grain, inclusion rules or timing create inconsistency.</li> <li>Design a remediation plan that prioritises the smallest set of changes that restore trust quickly: controlled definitions, certified datasets and quality gates.</li> <li>Implement checks in Great Expectations, focusing on freshness, key uniqueness, referential integrity and volume anomalies, and you will define what “fail closed” means so downstream reports do not publish partial numbers that look complete.</li> <li>Establish an operating route for backfills, including agreed replay windows and clear rules for when history may be rewritten, with dated notes so trend breaks can be explained without guesswork.</li> </ul> <p><strong>Security</strong><br /> Sensitive data stays in approved environments. Access is controlled through IAM roles and dataset entitlements, with time-bound elevation for troubleshooting and logged activity for review. Where segmentation is required, row-level rules are applied at the curated layer, and secrets are managed via a central key management service with rotation. You will document how data is handled and where it is stored so evidence can be assembled quickly without retrospective reconstruction.</p> <p><strong>Data quality and observability</strong><br /> Most engagements involve mixed cadence sources: daily operational feeds, weekly partner files and month-end corrections. You will define freshness expectations and backfill rules, including agreed replay windows and the conditions under which history may be rewritten. You will introduce lightweight monitoring so owners can see when a pipeline is late, a table is incomplete, or a quality threshold is breached, without needing a specialist to interpret logs.</p> <p><strong>Reward</strong><br /> Salary is negotiable. Benefits include 30 days holiday plus bank holidays, matched pension contributions, private medical cover, and a wellbeing programme with EAP. Notice periods are handled flexibly within reason, and a laptop plus approved peripherals are provided for secure working. Eligibility to work in the UK is required for the duration of employment.</p> <p><strong>Development</strong><br /> This is a role for someone who wants breadth without superficiality. You will be supported to deepen capability in governance tooling and quality engineering, including funded certification where it is directly relevant to delivery. Over time, you will lead larger remediation workstreams and mentor consultants on how to keep quality controls practical rather than theoretical.</p> <p><strong>Recruitment steps</strong><br /> The process includes an initial interview focused on problem framing and quality judgement, a scenario discussion covering a recurring reconciliation failure and an access exception, and a final conversation on communication and stakeholder handling. References are requested once an offer is accepted, and interview adjustments can be arranged when scheduling.</p> <p><strong>Working arrangement</strong><br /> Remote within the UK. Occasional travel for workshops is expected, typically one to two days per month at most, planned in advance and aligned to the point in delivery where it adds value.</p> <p class="job_tags">Tagged as: <a href="https://www.dataindex.co.uk/job-tag/data-consulting/" rel="tag">Data Consulting</a></p>
