Participate in finance transformation projects, acting as a single point of contact (SPOC) and contributing to general project management and execution.
Maintain and enhance existing dashboards, ensuring data accuracy and reliability.
Experience in data warehousing and business intelligence. - Basic knowledge of Extract, Transform, Load (ETL) processes.
Analyze complex business problems and issues using data from internal and external sources to provide insight to decision-makers
Perform data transformation using Power BI Query Editor and SQL Server Management Studio (SSMS).
Manage and optimize database components including views, CTEs, stored procedures, triggers, tables, and information schema.
Apply basic M-query knowledge for data shaping and transformation.
Develop and maintain DAX logic for advanced summarization, including pivoted and unpivoted transformations.
Integrate and manage diverse data sources such as SQL tables, SharePoint, Excel, JSON, etc.
Adhere to the software development life cycle (SDLC) and support business-as-usual (BAU) activities as needed.
Proactively identify and implement optimized solutions for data and reporting challenges.
Apply foundational knowledge of AI concepts including LLMs, agentic AI, statistical predictions, and Scikit-learn tools.
Utilize Python for data engineering tasks and automation.
Contribute to UI/UX design using tools like Figma or Adobe XD.
Build powerful visuals with story telling capabilities in Power BI
Skills & Tools
Power BI: DAX, M-query, Python integration
SSMS: SQL, DAX for SSAS
Design Tools: Figma, Adobe XD
Collaboration Tools: SharePoint
Productivity Tools: Excel, PowerPoint
Programming: Python
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Business Intelligence & AnalyticsRole: Business Intelligence & Analytics - OtherEmployement Type: Full time