Cleveland,OH,USA Posted: Tue, Mar 18 2025

• Design and Architecture: Look for evidence that they can translate business needs into a scalable BI solution (e.g., data models, ETL pipelines, dashboards).
• Data Engineering: Experience with data extraction, transformation, and loading (ETL/ELT) processes, working with tools like SQL, Python, or ETL platforms (e.g., Informatica, Talend).
• Data Warehousing: Proficiency in building and optimizing data warehouses or data lakes (e.g., Snowflake, Redshift, BigQuery).
• Visualization and Reporting: Expertise in BI tools like Power BI, Tableau, Qlik, or Looker, with a focus on user-centric dashboard design.
• Analytics: Ability to create advanced analytics solutions (e.g., predictive modeling, KPI reporting, or business forecasting).

• Database and Querying Skills: Advanced SQL knowledge and experience with relational and NoSQL databases.
• Cloud Platforms: Experience working with cloud BI ecosystems (e.g., Azure, AWS, or Google Cloud).
• APIs and Automation: Ability to integrate external systems via APIs and automate workflows.
• Programming Skills: Familiarity with Python, R, or similar for advanced analytics or data integration.
• Version Control: Experience with Git for managing BI codebases and collaborating with teams.

• Stakeholder Engagement: Evidence of collaborating with business teams to gather requirements, present insights, and iterate on solutions.
• Cross-Functional Collaboration: History of working closely with data engineers, analysts, and business teams to deliver seamless BI solutions.
• Communication: Ability to translate technical insights into actionable business strategies and present findings to non-technical stakeholders.
• Problem-Solving: Examples of addressing complex data challenges and delivering innovative BI solutions that drive value.