Data Analyst

Investigate end-to-end data flowsMap and investigate how data flows across source systems, pipelines, transformations, storage layers, interfaces, and downstream consumptionIdentify upstream and downstream dependencies, ownership gaps, handoffs, and critical integration points across domainsWork with multiple teams to understand how flows operate in practice, reconcile differences in understanding, and build a shared view of how data movesCreate clear analysis of how flows behave today, where they are fragile, and where complexity or duplication creates risk Assess impact of changesAnalyze what would happen if data flows, transformation logic, interfaces, schemas, or source-system behaviour were changedEvaluate impact on downstream reports, data products, operational processes, reconciliation, and business decisionsProvide structured change-impact assessments that help teams understand dependencies, break risks, and mitigation options before implementationHighlight where seemingly local changes could create broader cross-domain effects Build system and domain understandingDevelop deep understanding of key business domains, data entities, interfaces, and the meaning of the data as it moves across systemsNavigate multiple systems of record, inconsistent definitions, and domain-specific process variationsWork across business and technical stakeholders to validate how flows actually operate versus how they are documented, and communicate findings in a way that creates alignment Work across a hybrid landscapeInvestigate flows across legacy and modern platforms, including operational systems, EDW (SQL), Synapse, Databricks, and reporting layersUnderstand transitional architectures and how temporary solutions affect dependencies, continuity, and future-state designSurface fragmentation, redundant transformations, and weak control points that make change harder or riskier Make impacts visibleDocument data lineage, system dependencies, and change scenarios in a way that technical and business teams can useTranslate complex technical flow behaviour into clear risk, impact, and decision-support materialHelp teams understand where controls, validations, or additional analysis are needed before changes are approved Enable better cross-team decisionsPartner with engineers, architects, product teams, and business stakeholders to build shared understanding of data movement and impactFacilitate cross-team discussions to uncover dependencies, clarify ownership, and align on how critical flows work today and what may be affected by changeSupport change planning by identifying dependencies, required coordination, testing considerations, and sequencing needsDrive consistency in how flows, interfaces, and impacts are analysed and documented across teamsHelp teams ask the right questions before making changes to critical data paths Strengthen analysis disciplineEstablish structured ways to analyze lineage, dependencies, impact, and operational effects across critical flowsImprove the quality of flow documentation, change readiness assessments, and impact analysis across teamsPromote a more systematic understanding of how data changes affect business operations, controls, and downstream trust Stay close to the workWork directly with teams, documentation, systems, and subject matter experts to investigate real flow behaviour and resolve ambiguity What we're looking forMust-haveStrong experience analyzing complex data flows, system interactions, lineage, and dependencies across multiple platforms and domains including documented experience working with EDW (SQL), Synapse, Databricks, and reporting layersAbility to understand how data moves from source to consumption, including transformations, interfaces, controls, and handoffsProven experience performing impact analysis for changes to data structures, mappings, logic, integrations, or operating processesStrong understanding of hybrid data landscapes and how legacy and modern platforms coexist during transitionExcellent communication and stakeholder-management skills, with the ability to work across multiple teams and turn fragmented input into a clear, shared understandingExperience working across technical and business stakeholders to clarify definitions, validate behaviour, and resolve ambiguityAbility to structure and communicate complex dependencies, risk areas, and change consequences in a clear and usable wayStrong analytical thinking, with attention to detail and the ability to connect local changes to broader system and business impact MindsetCurious and persistent - digs until the real flow, dependency, or issue is understoodComfortable working in ambiguity and able to separate assumptions from verified behaviourAn excellent communicator who can build trust across teams, ask the right questions, and explain technical flow behaviour and impact in language others can act onSystem-minded and thoughtful about cause, effect, risk, and trade-offsFocused on improving decision quality, not just documenting complexity What success looks likeCritical data flows are better understood across teams and domains cross operational systems, EDW (SQL), Synapse, Databricks, and reporting layersTeams align faster on how flows work today and what changes may impactTeams can make changes with clearer understanding of downstream impact and upstream dependenciesHidden dependencies, fragilities, and ownership gaps are surfaced earlierImpact assessments are more consistent, useful, and actionable across the organisationChange-related incidents and unexpected downstream effects are reducedBusiness and technical stakeholders have greater confidence in how critical data moves and what depends on it