Data Analyst

Investigate end-to-end data flows
Map and investigate how data flows across source systems, pipelines, transformations, storage layers, interfaces, and downstream consumption
Identify upstream and downstream dependencies, ownership gaps, handoffs, and critical integration points across domains
Work with multiple teams to understand how flows operate in practice, reconcile differences in understanding, and build a shared view of how data moves
Create clear analysis of how flows behave today, where they are fragile, and where complexity or duplication creates risk
Assess impact of changes
Analyze what would happen if data flows, transformation logic, interfaces, schemas, or source-system behaviour were changed
Evaluate impact on downstream reports, data products, operational processes, reconciliation, and business decisions
Provide structured change-impact assessments that help teams understand dependencies, break risks, and mitigation options before implementation
Highlight where seemingly local changes could create broader cross-domain effects
Build system and domain understanding
Develop deep understanding of key business domains, data entities, interfaces, and the meaning of the data as it moves across systems
Navigate multiple systems of record, inconsistent definitions, and domain-specific process variations
Work 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 landscape
Investigate flows across legacy and modern platforms, including operational systems, EDW (SQL), Synapse, Databricks, and reporting layers
Understand transitional architectures and how temporary solutions affect dependencies, continuity, and future-state design
Surface fragmentation, redundant transformations, and weak control points that make change harder or riskier
Make impacts visible
Document data lineage, system dependencies, and change scenarios in a way that technical and business teams can use
Translate complex technical flow behaviour into clear risk, impact, and decision-support material
Help teams understand where controls, validations, or additional analysis are needed before changes are approved
Enable better cross-team decisions
Partner with engineers, architects, product teams, and business stakeholders to build shared understanding of data movement and impact
Facilitate cross-team discussions to uncover dependencies, clarify ownership, and align on how critical flows work today and what may be affected by change
Support change planning by identifying dependencies, required coordination, testing considerations, and sequencing needs
Drive consistency in how flows, interfaces, and impacts are analysed and documented across teams
Help teams ask the right questions before making changes to critical data paths
Strengthen analysis discipline
Establish structured ways to analyze lineage, dependencies, impact, and operational effects across critical flows
Improve the quality of flow documentation, change readiness assessments, and impact analysis across teams
Promote a more systematic understanding of how data changes affect business operations, controls, and downstream trust
Stay close to the work
Work directly with teams, documentation, systems, and subject matter experts to investigate real flow behaviour and resolve ambiguity
What we're looking for
Must-have
Strong 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 layers
Ability to understand how data moves from source to consumption, including transformations, interfaces, controls, and handoffs
Proven experience performing impact analysis for changes to data structures, mappings, logic, integrations, or operating processes
Strong understanding of hybrid data landscapes and how legacy and modern platforms coexist during transition
Excellent communication and stakeholder-management skills, with the ability to work across multiple teams and turn fragmented input into a clear, shared understanding
Experience working across technical and business stakeholders to clarify definitions, validate behaviour, and resolve ambiguity
Ability to structure and communicate complex dependencies, risk areas, and change consequences in a clear and usable way
Strong analytical thinking, with attention to detail and the ability to connect local changes to broader system and business impact
Mindset
Curious and persistent - digs until the real flow, dependency, or issue is understood
Comfortable working in ambiguity and able to separate assumptions from verified behaviour
An excellent communicator who can build trust across teams, ask the right questions, and explain technical flow behaviour and impact in language others can act on
System-minded and thoughtful about cause, effect, risk, and trade-offs
Focused on improving decision quality, not just documenting complexity
What success looks like
Critical data flows are better understood across teams and domains cross operational systems, EDW (SQL), Synapse, Databricks, and reporting layers
Teams align faster on how flows work today and what changes may impact
Teams can make changes with clearer understanding of downstream impact and upstream dependencies
Hidden dependencies, fragilities, and ownership gaps are surfaced earlier
Impact assessments are more consistent, useful, and actionable across the organisation
Change-related incidents and unexpected downstream effects are reduced
Business and technical stakeholders have greater confidence in how critical data moves and what depends on it

Work arrangement
No