Own the requirements-to-acceptance chain for the Entity Hub. This is a combined role: define what “correct” means for entity resolution and graph outputs, then prove it through structured testing. The position is pivotal because milestone payments are released against acceptance criteria — this role writes them, traces them and validates against them.
- Requirements & traceability — elicit, document and baseline functional and data requirements across ingestion, canonical model, entity resolution and graph serving; maintain a Requirement Traceability Matrix (RTM) from requirement through to test evidence.
- Acceptance criteria ownership — translate SOW stage acceptance criteria into testable, measurable conditions; secure WK agreement on match-quality measures (precision/recall) and NLQ scenarios before build begins.
- Test strategy & planning — define the overall test strategy, quality gates, entry/exit criteria and test data approach for each milestone.
- Data quality validation — design and execute tests for data completeness, accuracy, transformation logic, standardization rules and identifier-spine integrity across all six sources.
- Entity resolution validation — build and curate labelled/golden validation samples; evaluate match precision, recall and false-positive rates; validate clustering and Golden Record survivorship logic.
- Graph validation — test node and edge accuracy, source traceability, and multi-hop traversal scenarios against expected paths.
- Human-in-the-loop coordination — operate and coordinate the SME review workflow, manage the review queue, capture reviewer decisions and feed them back as training/tuning input.
- Defect management — log, triage and track defects with reproducible steps; drive root-cause analysis on data discrepancies; maintain severity classification and closure evidence.
- UAT & sign-off — plan and coordinate user acceptance testing with WK SMEs; assemble milestone acceptance packs and secure written sign-off within the agreed review window.
Required Skills & Experience
Skill Area Specific Requirements Business Analysis Requirements elicitation, user stories, functional specifications, RTM, data dictionaries, source-to-target mapping documentation QA / Testing Test strategy, test planning, test case design, regression suites, UAT coordination, defect lifecycle management Data Testing Advanced SQL for reconciliation, source-to-target validation, aggregation and business-rule testing, data integrity and constraint checks Platform Microsoft Fabric (Lakehouse, Delta tables, pipelines), OneLake, SQL analytics endpoints Domain (advantageous) Entity/master data concepts, match precision & recall, data quality dimensions, corporate hierarchy and ownership data Tools Test management platforms (QTest/Jira/ADO), Excel, Postman for API validation, Power BI for validation reporting Soft Skills Client-facing communication, stakeholder facilitation, precision in written acceptance language, structured escalationQualifications
- 6+ years combined Business Analysis and QA experience on data platform or data warehouse programmes
- Demonstrable experience writing acceptance criteria that were used for formal client sign-off
- Strong SQL — able to independently write reconciliation and validation queries
- Experience maintaining a Requirement Traceability Matrix on a regulated or enterprise client engagement
- Experience coordinating UAT with external client stakeholders
Nice-to-Have
- Exposure to entity resolution, MDM or data-matching projects
- Familiarity with Microsoft Fabric or Azure data services
- Understanding of graph data structures (nodes, edges, traversal)
- Experience with statistical quality measures (precision, recall, F1)
Key Deliverables Owned
- Requirement Traceability Matrix (RTM)
- Test Strategy, Test Plans, Test Scenarios and Test Cases
- Entity resolution evaluation results and match-quality reports
- Node/edge accuracy validation evidence
- Defect log, RCA reports and closure evidence
- UAT sign-off and milestone acceptance packs
Dual Role / Complementary Skills
This is already a deliberate dual role (BA + QA). The pairing is intentional: the person who defines acceptance criteria is best placed to test against them, creating a tight traceability loop and removing hand-off ambiguity. Complementary overflow: this role can absorb a portion of project-coordination and documentation work alongside the Project Manager (who is at 75% FTE).
Skills Required
- 6+ years of combined Business Analysis and QA experience on data platform or data warehouse programs
- Requirements elicitation, user stories, functional specifications, requirement traceability matrices, data dictionaries, and source-to-target mapping documentation
- Test strategy, test planning, test case design, regression suites, UAT coordination, and defect lifecycle management
- Strong SQL skills for reconciliation and validation queries
- Advanced SQL for source-to-target validation, aggregation, business-rule testing, data integrity, and constraint checks
- Experience writing acceptance criteria used for formal client sign-off
- Experience maintaining a Requirement Traceability Matrix on a regulated or enterprise client engagement
- Experience coordinating UAT with external client stakeholders
- Client-facing communication, stakeholder facilitation, precise written acceptance language, and structured escalation
- Experience with Microsoft Fabric, including Lakehouse, Delta tables, pipelines, OneLake, and SQL analytics endpoints
- Experience with test management platforms such as QTest, Jira, or Azure DevOps
- Experience with Excel, Postman for API validation, and Power BI for validation reporting
- Exposure to entity resolution, master data management, or data-matching projects
- Familiarity with Microsoft Fabric or Azure data services
- Understanding of graph data structures, including nodes, edges, and traversal
- Experience with statistical quality measures including precision, recall, and F1
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.







