Enterprise architect

We are looking for a skilled Data Migration Architect to join our team and lead the transition from legacy Oracle systems to Microsoft Fabric. As a key member of our data team, you will be responsible for the following tasks:

• Legacy system analysis: Audit existing on-premises Oracle schemas, stored procedures, and Snowflake models to identify business logic and data dependencies.

• Migration Strategy & Roadmap: Design a phased transition plan from Oracle to Fabric, ensuring data parity, minimal business downtime, and a clear "cut over" strategy.

• Medallion architecture design: Architect the three-tier (Bronze, Silver, Gold) structure within Microsoft Fabric, ensuring data is optimized for both raw storage and business intelligence.

• ETL/ELT orchestration: Design ingestion pipelines using Data Factory and Fabric Notebooks to move data from on-prem Oracle to OneLake.

• Performance optimization: Implement advanced Fabric features such as V-Order, partitioning, and Liquid Clustering to ensure optimal query performance.

• Governance & security: Establish data security protocols, access controls (RLS/OLS), and metadata management using governance tools (Microsoft Purview, Microsoft Fabric and 3rd party).

• Strategic guidance: Contribute to the organizational data strategy, including standards of data quality, the flow of data within the organization, and security of data.

If you are a data expert with a passion for architecting efficient and secure data migration solutions, we invite you to apply for this exciting opportunity. Join us in shaping the future of our data infrastructure and making a meaningful impact on our organization's success.

Following skills and knowledge are required for the performance of the tasks:

• Data analysis: proven expertise in identifying critical data elements from business processes, key business intelligence products, and data profiling.

• Data warehouse design

• Relational vs. distributed mastery: Ability to bridge the gap between traditional RDBMS (Oracle) and distributed data processing (Spark/Delta Lake).

• Advanced data modeling: Expert-level knowledge of Kimball methodologies, Star Schemas, Snowflake modeling, Parquet format, handling Slowly Changing Dimensions (SCD), and Change Data Capture ingestion pattern. Proven expertise in designing data models of different levels of complexity and detail: from conceptual data model down to logical and physical data model, from enterprise data models to solution-specific data models.

• SQL & programming: Deep proficiency in Oracle PL/SQL for legacy analysis and Spark SQL/Python (PySpark) for modern transformations.

• Communication: Ability to explain complex architectural shifts to stakeholders and translate business requirements into technical blueprints. Ability to interface effectively with users, technical staff, and (senior) management.

• Languages: Good knowledge of written/spoken English (working language). Knowledge of French is an asset.

• Capability of integration in an international/multicultural environment, rapid self-starting capability, and experience in working in a team.

• Ability to participate in multilingual meetings.

• Ability to work in a multi-cultural environment, on multiple large projects.

• Excellent Team Player.

• High degree of discretion and integrity is required as the applications managed and maintained in HR.A5 contain personal and confidential data.

• Oracle migration: Proven experience migrating large-scale Oracle workloads (12c/19c) to cloud environments.

• Microsoft Fabric stack: Hands-on experience with OneLake, Lakehouse/Warehouse items, and the import mode in Power BI.

• Delta Lake features: Deep understanding of Delta Lake ACID transactions, time travel, and schema evolution.

• Data Lakehouse optimization: Specific expertise in optimizing Spark compute clusters and SQL Analytics endpoints for high-concurrency reporting.

• Microsoft Certified: Azure Data Engineer Associate (DP-203) – required.

• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) – a plus.