Data Management Analyst

Instant Impact

. Deliver data quality and data governance initiatives, including data profiling, validation, reconciliation, and root-cause analysis across structured and unstructured datasets .

Posted 11/6/2026full-timeCracow • PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data quality and governance initiatives, including metadata management and data profiling, while effectively collaborating with stakeholders to enhance data controls and improve data handling processes.

Highest-signal resume keywords

Data Quality ManagementMetadata ManagementSQL ProficiencyPython ProficiencyData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ProfilingData ValidationData ReconciliationData Quality Rules DevelopmentData Quality Metrics MonitoringMetadata Standards ImplementationData Lifecycle ManagementData AnalysisData Catalogue ManagementData Control Frameworks

Soft Skills

Strong CommunicationStakeholder ManagementAttention to DetailOrganizational SkillsProblem-Solving

Tools & Technologies

Data Quality ToolsData Catalogue ToolsAzureAutomated PipelinesData Governance Tools

Industry Keywords

Critical Data ElementsData StewardshipUnstructured DatasetsData LineageBusiness Glossary Management

Tech Stack

Tools & technologies

AzureCloudPythonSQL

About the role

Key responsibilities & impact

Deliver data quality and data governance initiatives, including data profiling, validation, reconciliation, and root-cause analysis across structured and unstructured datasets
Identify and document Critical Data Elements (CDEs), including definitions, ownership, business rules, and authoritative sources
Develop and maintain data quality rules, controls, and thresholds using enterprise data quality tooling
Define and monitor data quality metrics, supporting remediation activities and continuous improvement plans
Work with Data Stewards and business stakeholders to resolve data quality issues and strengthen data controls
Maintain and enhance the enterprise data catalogue, ensuring data assets are accurately documented and easily discoverable
Implement and manage metadata standards, including classification, lineage, taxonomies, ownership, and usage guidance
Develop and maintain business glossaries and ensure metadata remains accurate and aligned to regulatory requirements
Promote data catalogue adoption and increase metadata awareness across business functions
Partner with Data Engineering teams to embed data quality controls and metadata capture into automated pipelines
Support lineage capture and transparency across data platforms and data flows
Contribute to governance forums, working groups, and data management initiatives
Recommend improvements to data handling, control frameworks, and operational processes
Support AI readiness by ensuring data assets are well-documented, controlled, and of high quality

Requirements

What you’ll need

Proven experience in data quality, metadata management, data governance, or a related data management discipline
Hands-on experience with data quality and data catalogue tools, including profiling, rule management, lineage capture, glossary management, and metadata enrichment
Strong understanding of metadata concepts, including classification, lineage, taxonomies, ontology modelling, and business glossary management
Strong SQL and Python skills for data analysis, profiling, reconciliation, and control development
Understanding of modern cloud-based data platforms, particularly Azure and associated data architectures
Experience working with both structured and unstructured datasets
Knowledge of data lifecycle management, authoritative data sources, and data control frameworks
Ability to analyse complex data issues and translate findings into practical improvement actions
Strong communication and stakeholder management skills
Excellent attention to detail and organisational skills
Comfortable working in a growing or evolving data environment and helping shape processes, standards, and controls