Expert BI and Data Analyst Consultant

Mission Overview:

Keystone Solutions is seeking an expert Data Analyst for a consultancy mission in Brussels. You will be hired by Keystone Solutions and represent us on-site within our client's Corporate Banking transformation environment, working under the guidance of the client's Cluster Product Owner. The mission focuses on shaping the future of Corporate Banking data intelligence by modernising the BI and reporting ecosystem from SAS/SQL, Alteryx and JavaScript/React towards a future-proof Power BI platform integrated with Microsoft Dynamics 365. This is a strategic reinvention of how data flows, insights are delivered and business value is unlocked for Sales, Metiers and Leadership teams.

Consultancy Responsibilities:

Under Keystone Solutions' consultancy model, you will carry out the following responsibilities while representing Keystone Solutions in the client environment:

• Strategic Banking Transformation: Lead end-to-end banking data transformations, focusing on strategic planning and migration from legacy ETL workflows to Power BI-centric architectures.
• Drive adoption roadmaps for scalable, future-proof BI solutions aligned with enterprise data governance and regulatory requirements.
• Power BI Architecture and Team Upskilling: Design and enforce a scalable Power BI architecture.
• Coach and mentor team members to adopt Power BI best practices, including performance optimisation, security and deployment strategies.
• Upskill teams in advanced DAX development, including complex calculations, time intelligence and dynamic measures, as well as Power Query/M for efficient data transformation and custom functions.
• Promote reusable templates, standardised patterns and collaborative development, including shared datasets and Power BI Premium capacities.
• Data Modeling and Analytical Framework: Translate business requirements into optimised data models for analytics and reporting.
• Apply dimensional modelling, including star and snowflake schemas, to simplify cross-platform complexity.
• Design logical and physical data layers that ensure performance, scalability and maintainability.
• Manage metadata for traceability, including lineage, ownership and refresh cycles.
• ETL Pipeline and Data Integration: Own source-to-target mapping and ETL/ELT pipeline optimisation.
• Use SAS, SQL and Denodo VQL for high-performance data extraction, transformation and loading.
• Implement data quality controls, including validation rules, anomaly detection and reconciliation processes.
• Ensure seamless integration of new data sources with minimal latency and maximum reliability.
• Documentation and Governance: Establish and enforce documentation standards for datasets, including business definitions, technical specifications and refresh policies.