Financial Systems Analyst

Job Responsibilities:

Dataset Consolidation: Integrate and consolidate datasets from various sources within MS Fabric to ensure data consistency and accuracy. Dataflow Development: Design, build, and maintain dataflows in MS Fabric to automate data processing and transformation tasks. Python Notebooks: Utilize Python notebooks within MS Fabric to perform data analysis, create visualizations, and develop new semantic models. Semantic Modeling: Generate and maintain semantic models to support business intelligence and analytics initiatives. Collaboration: Work closely with data engineers, data scientists, and business analysts to understand data requirements and deliver solutions that meet business needs. Documentation: Document dataflows, processes, and models to ensure knowledge sharing and maintainability. Performance Optimization: Monitor and optimize the performance of dataflows and models to ensure efficient data processing. Skills:

Python-based AI models within the Fabric environment Someone that knows the AI deployment use case Consolidate disparate datasets and build semantic models in Fabric and Can build data pipeline that can execute python notebooks(LLM or Ai predictive models) within Fabric. Education/Experience:

Proficiency in MS Fabric: Extensive experience working with Microsoft Fabric, including dataset consolidation, dataflow development, and Python notebooks. Data Integration: Strong understanding of data integration techniques and best practices. Python Programming: Proficiency in Python for data analysis, scripting, and automation. Data Modeling: Experience in creating and maintaining semantic models for business intelligence and analytics. Analytical Skills: Strong analytical and problem-solving skills to identify and resolve data-related issues. Collaboration: Excellent communication and collaboration skills to work effectively with cross-functional teams. Documentation: Ability to document processes, dataflows, and models clearly and concisely. Experience with BI Tools: Familiarity with business intelligence tools such as Power BI, Tableau, or similar. Cloud Platforms: Experience working with cloud platforms such as Azure, AWS, or Google Cloud. SQL: Proficiency in SQL for querying and managing relational databases. Data Governance: Understanding of data governance principles and practices.