What you will do
- Design, develop, and maintain Enterprise Data Warehouses (EDW), Data Lakes, and Data Lakehouse solutions to support enterprise reporting and analytics.
- Design and implement modern BI architectures across cloud, on-premises, and hybrid environments, ensuring scalability, security, and data residency compliance.
- Gather and analyse business requirements related to data pipelines, data storage, reporting, and analytics solutions.
- Develop and manage ETL/ELT processes and data orchestration workflows to integrate data from multiple sources.
- Implement data contracts and schema evolution management to ensure reliable and consistent data pipelines.
- Design and implement data virtualization layers to provide unified access to multiple heterogeneous data sources.
- Develop and maintain dimensional data models, including Star Schema and Snowflake Schema, to support business intelligence and reporting requirements.
- Design, develop, and maintain interactive dashboards, reports, KPIs, and self-service BI applications.
- Optimize physical database schemas through indexing, partitioning, and storage management techniques.
- Perform database performance tuning, SQL query optimization, and resource utilization improvements to meet performance SLAs.
- Implement data quality frameworks, data validation processes, and data observability mechanisms to monitor data freshness, lineage, and pipeline health.
- Define and execute testing strategies for BI solutions, including data validation, regression testing, contract testing, and automated testing.
- Integrate automated testing and deployment processes into CI/CD pipelines.
- Prepare and maintain technical documentation, including data dictionaries, data lineage, architecture specifications, and operational runbooks.
- Manage BI platform deployment, configuration, and environment management using Infrastructure as Code and version control practices.
- Govern BI semantic layers, including KPI definitions, metrics catalogues, naming conventions, and row-level security.
- Implement and manage access controls and data security policies in accordance with GDPR and organizational standards.
- Optimize BI platforms and data warehouses for performance and cost efficiency using caching, clustering, partitioning, and resource scaling.
- Establish data lineage, data stewardship, and governance practices to ensure transparency, auditability, and regulatory compliance.
- Enable self-service BI by providing curated datasets, certified reports, and appropriate user training and support.
What you bring
- Strong experience in Business Intelligence development, Enterprise Data Warehousing, and modern data analytics solutions.
- Good knowledge of Enterprise Data Warehouse architecture and dimensional data modelling.
- Experience designing Star Schema, Snowflake Schema, and logical and physical data models.
- Understanding of Data Lake and Data Lakehouse architectures, including Delta Lake and Apache Iceberg.
- Excellent knowledge of SQL and relational database systems used in enterprise data warehousing.
- Knowledge of NoSQL and distributed database technologies such as MongoDB, Cassandra, and Hadoop HBase.
- Hands-on experience with BI reporting and visualization tools such as Power BI, Tableau, and Qlik.
- Experience with ETL/ELT tools and data integration platforms such as Informatica, Talend, dbt, and Azure Data Factory.
- Familiarity with data modelling and architecture tools such as ERwin, SAP PowerDesigner, and ArchiMate.
- Knowledge of OLAP technologies such as SQL Server Analysis Services (SSAS) and Essbase.
- Familiarity with data mining tools such as SAS Enterprise Miner and RapidMiner.
- Experience with near-real-time data ingestion and Change Data Capture (CDC) technologies such as Apache Kafka, Debezium, and Oracle GoldenGate.
- Knowledge of cloud-based BI and data warehouse platforms such as Azure Synapse, Snowflake, and Amazon Redshift.
- Understanding of data governance and metadata management tools such as Collibra, Alation, and Microsoft Purview.
- Knowledge of data observability practices, including data freshness monitoring, lineage tracking, and anomaly detection.
- Understanding of CI/CD, version control, automated testing, and deployment management for BI solutions.
- Knowledge of data security, GDPR compliance, access management, and row-level security.
How you work
- Translate business requirements into scalable BI architectures, data models, and reporting solutions.
- Design and maintain reliable, high-performing data pipelines and enterprise reporting platforms.
- Develop optimized SQL queries and troubleshoot database and data warehouse performance issues.
- Apply consistent development standards and quality practices throughout the BI development lifecycle.
- Ensure data accuracy, consistency, reliability, and traceability across reporting solutions.
- Identify performance bottlenecks and implement appropriate optimization strategies.
- Communicate technical concepts and analytical insights effectively to business and technical stakeholders.
- Collaborate with Data Engineers, Data Architects, Business Analysts, and business users.
- Manage multiple BI development activities and deliver solutions within agreed timelines.
- Promote self-service analytics and enable business users to access trusted data and reporting solutions.
- Adapt to evolving BI technologies, cloud platforms, and modern data engineering practices.
- Work effectively in international and multicultural environments.
- Participate in multilingual meetings and communicate fluently in English; knowledge of French or Dutch is an added advantage.
- Demonstrate strong interpersonal, communication, analytical, and problem-solving skills.
- Work independently as well as collaboratively within cross-functional teams.
What you can expect
- Opportunities to work on enterprise-level Business Intelligence and data transformation initiatives.
- Exposure to modern cloud data platforms, Data Lakes, Lakehouses, and Enterprise Data Warehousing solutions.
- Opportunities to work with advanced BI reporting, analytics, and data integration technologies.
- Collaboration with Data Architects, Data Engineers, and business stakeholders.
- Opportunities to contribute to enterprise reporting strategies and self-service analytics solutions.
- A professional environment that encourages continuous learning and technical development.