Senior Business Intelligence Developer

Description:

The Senior Business Intelligence (BI) Developer is instrumental in developing enterprise analytics and data solutions and providing technical support for the enterprise data management platform. Using deep experience in implementing scalable analytics on modern data platforms, the role supports enterprise data capabilities such as data integration, analytics enablement, enterprise data modelling, governance, and data quality across hybrid data architectures (cloud and on-premises).

This position:
Develops, enhances and supports complex data solutions, tools and automations, partnering closely with internal business units and technical teams
Involves working on multiple enterprise initiatives focused on the implementation of new or enhanced systems, solutions and processes.
Translates business requirements into technical specifications and implements secure, scalable, and compliant data and analytics solutions

What you do:

Work with business stakeholders and internally across the department to scope initiatives, including functional and technical deliverables, cost estimates, resource requirements, and expected benefits.
Participate in analysis, planning and development of detailed roadmaps for modernization of the VFPA enterprise data platform.
Share technical ownership of the organization's data platform with team members, supporting both on-premises and cloud-based environments.
Work closely within the information services team and as part of project teams to design, implement, and test data models and data management systems.
Contribute to the definition and evolution of enterprise data models, standards, and metadata practices to support consistent, governed use of data across the organization.
Implement and maintain technical data quality checks and validation controls within the modern data platform, analytical models, and semantic layers, based on defined business rules and governance standards
Support the full analytics lifecycle including data design, data integration, validation and reporting using Agile or Waterfall methodologies.
Ensure upgrades and changes to VFPA’s data infrastructure align with IS department’s service level standard.
Research new technologies, implement proofs of concept/MVPs and make recommendations to build scalable and supportable infrastructure, as appropriate.
Perform root-cause analysis for service interruption and develop solutions to complex technical problems and take appropriate urgent actions.
Support the maintenance of data infrastructure: database servers, performance monitoring, security configuration, database software (SQL): installation, patching, upgrades, decommissioning etc.
Assist with data backup, recovery, high availability and disaster recovery procedures to ensure business continuity.
Support implementation of and maintain database security controls (user access, roles and privileges) and audit functions.
Plan storage and capacity to support ingestion of raw data sources into the VFPA data platform.
Monitor, tune and optimize database and report performance.
Create or modify database objects, procedures, and scripts as needed to support analytics and data platform requirements.
Provide secondary support for database platform administration in collaboration with the primary DBA to ensure operational continuity.
Configure, perform and monitor system level backups and restore via enterprise level backup solutions
Participate in the analysis, and documentation of analytics solutions from design through to implementation.
Create, enhance and document conceptual, logical and physical database models to support analytics, reporting and enterprise data consistency.
Develop data transformation and integration logic to deliver curated datasets and analytical models that support enterprise reporting and decision-making.
Implement automated data validation and quality checks within data transformation, integration and analytical models to ensure accuracy, completeness, and consistency of datasets.
Define and maintain business and technical metadata, including data definitions and lineage, to support data discovery, understanding and reuse.
Create and maintain enterprise semantic layers to support reporting, dashboards, and analytics.
Participate in forming strategies for VFPA data availability, security, archival, recovery and migration.
Design, build and deploy dashboards and analytical reports.
Develop analytical calculations and business logic to support reporting and self-service analytics.

What you bring:

Must have a degree in Information Technology or an acceptable degree in a related field
A minimum of 5 years of senior BI development experience in an enterprise environment.
A minimum of 3 years of hands-on experience designing, building and supporting enterprise data solutions with Microsoft Fabric environment, including Lakehouse, Warehouse OneLake, Data Factory orchestration, semantic modeling, and deployment across development and production environments.
Must have demonstrated experience with physical and logical design of database architecture for relational databases, data warehouses and data lakes.
Must have demonstrated experience with database optimization, data replication, database recovery and performance tuning.
Must have expertise in data warehousing and data integration: dimensional modelling, facts, dimensions, helper tables, SCD concepts etc.
Must have experience working with enterprise data models, data dictionaries, metadata/cataloging platforms and technical data quality controls in a governed analytics environment.
Must have demonstrated experience with the development of enterprise semantic models and analytical datasets.
Must have an understanding of dashboard deployment models across on-premises and cloud environments.
Must have strong SQL skills and experience with analytical expressions (e.g. DAX)
Must have experience with Azure DevOps or Git-based source control, including CI/CD pipeline implementation and deployment automation.
Must have experience with:
Functional programing languages (R, Python etc.), APIs and web services.
Data security principles, efficiency, quality and governance.
Complex technical and architectural documentation skills.