Data Engineering & Analytics consultant

The client is a Nordic investment bank and investment firm with operations in Norway and Sweden, providing capital markets services across investment banking, equities, fixed income, foreign exchange, derivatives and investment research. They support corporate, institutional and private clients with financing, advisory services, securities trading, hedging solutions and capital and debt market insight. They aim to be a leading Nordic capital markets platform through sector expertise, execution capability and close cooperation with owner banks, combining strong local distribution with Nordic reach and international investor access.

• Solid understanding and hands-on experience with data modelling including scalable semantic models, reusable data products, and reporting-ready data structures
• Experience with financial data domains such as market data, static data, transactional data, AML/KYC, positions, and accounting data
• Experience with end-to-end data engineering in a cloud-based modern data platform, preferably Microsoft Fabric
• Proven experience working with technical and non-technical stakeholders in complex organizations involving data, insights, reporting, and/or automation initiatives
• Good understanding of key data governance principles including data ownership, lineage, quality, classification, access control, and auditability
• Experience implementing or advising on security, confidentiality, role-based access control, and segregation of duties
• Ability to translate business needs into well-defined data sets, reporting layers, exports, and operational automation use cases
• Strong communication skills and ability to work independently with various stakeholders including business, operations, IT, risk, compliance, finance, and front-office

Nice to Have:

• Familiarity with Microsoft Fabric, Azure Data Lake, Synapse, Power BI, and related Microsoft data platform services
• Experience from regulated environments such as finance, compliance, risk, security, or other control- and reporting-heavy domains
• Experience integrating financial, trading, CRM, identity, or third-party source systems into governed data and reporting platforms

Microsoft Fabric Data Engineering:

• Ingest data from external source systems into Microsoft Fabric using robust, maintainable pipelines
• Design and implement transformations, curated data layers, and reusable data products suitable for analytics and operational use
• Develop and maintain data quality tests, validation routines, and reconciliation controls
• Document data lineage, dependencies, refresh logic, and operational ownership for Microsoft Fabric solutions

Financial Data Modelling:

• Model financial data domains including market data, static data, transactional data, AML/KYC data, positions, and accounting data
• Translate business concepts and financial data definitions into scalable semantic models and reusable reporting structures
• Ensure consistent handling of identifiers, hierarchies, time dimensions, ownership, historization, and source-system keys
• Collaborate with business, IT, risk, compliance, and finance stakeholders to clarify data meaning, usage, and control requirements

Security, Data Governance & Access Control:

• Advise on and implement security, data governance, and access control principles
• Manage confidential data per internal policies and regulatory requirements
• Define and implement role-based access control, workspace governance, data classification, and segregation of duties
• Support auditability through documentation of permissions, data handling principles, control points, and ownership

Reporting, Export Layer & Operational Automation:

• Translate business needs into data sets for reporting, exports, analytics, and operational automation
• Design and maintain reporting and export layers with clear definitions and stable structures
• Ensure data sets are reliable, well-documented, and fit for business-critical use cases
• Identify opportunities to standardize reports, extracts, and operational processes through governed data products

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