Data Engineer

Data Engineer

Cincinnati, Ohio Onsite (5 days)

Full time

Intelligence Developer Job Description

Proficiency in Power BI: Including data modeling, DAX, Power Query, and report/dashboard design.

SQL Knowledge: For data querying and manipulation.

Data Warehousing: Understanding principles like ETL and data modeling concepts.

Minimum Knowledge, Skills, and Abilities Required:

• Bachelor's degree in computer science/information systems or equivalent combination of education and experience.
• Strong communication skills- Must be able to communicate ideas both verbally and in writing to management, business and IT sponsors, and technical resources in language that is appropriate for each group.
• Excellent analytical and problem-solving skills when resolving data related issues or designing new solutions.
• Experienced in SDLC and can assist in Project Management. Able to understand release management protocols and manage important tasks for implementation.
• Power BI Proficiency: Deep knowledge and experience with Microsoft Power BI, including Data Modeling: Designing and building data models within Power BI, understanding relationships, and optimizing performance. DAX (Data Analysis Expressions): Writing complex DAX formulas to perform calculations, define measures, and create derived columns. Power Query (M Language): Using Power Query to connect to various data sources, transform, and clean data. Report & Dashboard Design: Creating visually appealing, user-friendly, and informative reports and dashboards that effectively communicate insights. Data Visualization: Choosing appropriate chart types, designing layouts, and effectively presenting data through compelling visualizations.
• SQL: Strong understanding of SQL for querying databases, extracting data, and data manipulation.
• Data Warehousing Concepts: Familiarity with data warehousing principles, star schemas, snowflake schemas, and ETL processes.
• Data Sources: Experience connecting to and working with a variety of data sources (e.g., SQL Server, Excel, Azure SQL Database, cloud-based data sources).
• Performance Optimization: Ability to identify and resolve performance issues in Power BI reports and data models.