Senior Data Analyst

Role: Senior Data Analyst

Job Type: Hybrid (Contract)

Contract Duration: 6 Months & Its extendable

Location: Remote Copenhagen, Denmark

Note: This is a Contract Role.

Job Description

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

What you'll do

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