Business Intelligence Specialist

Description:

Following tasks will be performed by external service provider:

• Creation and maintenance of Enterprise Data Warehouses (EDW) and complex Business Intelligence Solutions (Data Lakes / Data Lakehouse).
• Designing architectures both on the cloud and on premises (whether hosting or cloud on-premises) or combination of both (hybrid).
• Design a modern scalable data platform to replace a large legacy data system in a phased approach.
• Align architectural decisions with data governance policies and the department’s vision on cloudification.
• Design of data quality, audit and health monitoring processes.
• Define best practices, standards, rules, policies, review processes. Ensure regulatory compliance.
• Provide guidance and mentorship to data analysts, data engineers.
• Facilitate change management by guiding colleagues and users through the migration process.
• Document and maintain data architecture and data assets in detail.
• Elaboration of test programs.
• Assistance with deployment and configuration of the system.
• Participation in meetings with other project teams.

Knowledge And Skills:

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

• Experience in migrating legacy data systems to a modern data platform.
• Excellent knowledge of designing scalable and flexible modern data architectures.
• Excellent knowledge of business intelligence reporting tools.
• Strong understanding of cloud data architecture principles.
• Knowledge of database systems, both relational (PostgreSQL, Oracle) and non-relational (Elasticsearch, MongoDB).
• Experience with ETL/ELT processes, API integration, data ingestion and transformation tools (dbt, Spark, Talend, Fabric, SAP DS).
• Proficiency in data pipeline orchestration tools (Airflow, Dagster).
• Knowledge of data governance frameworks and tools (Datahub, Open Metadata, Atlas, Collibra), data quality management, data security, access control and regulatory compliance.
• Experience with DevOps practices and tools related to data pipelines, including CI/CD for data infrastructure.
• Excellent communication skills to articulate data architecture concepts to technical and non-technical stakeholders.
• Good knowledge of modelling tools.