Data Analyst Finance

Job Summary: The Data Analyst/Developer will play a crucial role in developing automated data solutions, creating comprehensive dashboards, and utilizing advanced Excel functionalities. This position will require collaboration with various teams to translate data needs into actionable intelligence. Key Areas of Expertise and Responsibilities: 1. Visual Basic for Applications (VBA) Responsibilities: Develop and maintain complex VBA applications to automate repetitive tasks. Incorporate SAP Scripting within VBA to optimize business processes. Troubleshoot and debug existing VBA code to ensure smooth functionality. Criteria: Advanced proficiency in VBA programming. Demonstrated experience with SAP interfaces and scripting. Ability to write modular, efficient, and maintainable code. Knowledge of Excel object model and its functionalities. 2. Power Query Responsibilities: Utilize Power Query for data extraction, transformation, and loading (ETL) processes. Develop and maintain data models in Excel to streamline data preparation. Create and optimize Power Query scripts for efficient data processing. Criteria: Intermediate experience with Power Query including M language for data transformation. Familiarity with connecting Power Query to various data sources (e.g., databases, APIs). Ability to perform data cleansing and manipulation through Power Query. 3. Power BI Responsibilities: Create interactive, user-friendly dashboards and reports using Power BI. Collaborate with stakeholders to gather reporting requirements and deliver insights. Optimize Power BI reports for performance and usability. Criteria: Intermediate knowledge of Power BI Desktop and Power BI Service. Ability to create DAX measures and calculated columns for enhanced analytics. Familiarity with data visualization best practices and techniques. 4. Python Responsibilities: Develop Python scripts to automate data manipulation and Excel-related tasks. Utilize libraries such as Pandas and NumPy for data analysis and automation. Collaborate with the data team to integrate Python solutions with existing tools. Criteria: Intermediate proficiency in Python, especially in data manipulation and automation. Experience with libraries like Pandas, NumPy, and openpyxl for Excel automation. Understanding of APIs and ability to retrieve data programmatically. Qualifications: Bachelor's degree in computer science, Data Science, Statistics, Mathematics, or a related field. A minimum of 4 of experience in a data-related role, focusing on the technologies mentioned. Strong analytical and problem-solving skills with attention to detail. Excellent communication skills and the ability to work collaboratively with diverse teams. Preferred Skills: Experience with SQL and relational databases for data querying and data management. Familiarity with other business intelligence tools (like Tableau or QlikView) is a plus. Knowledge of machine learning principles is an advantage. Understanding of data warehousing concepts and methodologies.

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