Business Intelligence Developer

Job Description

• Hands-on experience with Cognos Analytics and Power BI, including DAX, data modeling, and report migration.

• Strong Python skills for data manipulation, automation, and analytics.

• Experience with Microsoft Fabric (Lakehouse, Warehouse, semantic models).

• Experience with Azure data platforms, including Databricks and Azure Data Lake.

• Strong SQL and data warehousing fundamentals.

• Familiarity with ETL / ELT tools (Informatica experience a plus).

• Strong analytical, problem-solving, and communication skills.

• Comfortable working in a transformational, fast-evolving environment.

• Financial Services experience preferred.

Responsible for supporting business intelligence and analytics needs within the Client, partnering with business stakeholders and contributing to the transformation from a legacy on-prem BI environment (DB2 / Informatica / Cognos) to a modern Azure and Microsoft Fabric–based analytics platform (Databricks, Fabric, Power BI). This role will focus on developing modern BI solutions while supporting and migrating existing Cognos assets.

Job Responsibilities

• Develop and support dashboards and reports using Power BI (primary) and Cognos Analytics (legacy support during the transition).

• Lead and support migration of reports, dashboards, and data models from Cognos to Power BI / Microsoft Fabric, ensuring accuracy, performance, and consistency.

• Design and build scalable Power BI semantic models aligned with Microsoft Fabric and modern BI best practices.

• Use Python for data transformation, automation, and analytics within Databricks and Microsoft Fabric environments.

• Collaborate with Data Engineering teams to support Fabric Lakehouse and Warehouse solutions and Azure-based data pipelines.

• Provide production support and root cause analysis across legacy and modern BI platforms.

• Convert end-user reporting solutions (Excel, Access, SAS) into governed, automated Power BI solutions.

• Gather, document, and translate business requirements into technical specifications, including data mappings and transformation logic.

• Support unit testing and UAT, ensuring data quality and reporting accuracy.

• Provide guidance and enablement for Power BI self-service analytics.

• Support enterprise analytics transformation initiatives and evolving BI standards.