Huron Hiring Analytics Engineer - Analyst

About the Role

As a member of the Huron corporate team, you will help evolve our business model to stay ahead of market forces, industry trends, and client needs. Our accounting, finance, human resources, IT, legal, marketing, and facilities management professionals work collaboratively to support Huron's collective strategies and enable real transformation to produce sustainable business results.

In the Data and Analytics Analyst role, you will work with Data Engineers, Power BI Developers, Data Architects, QA teams, team leads, and business stakeholders to support Huron's enterprise analytics and reporting solutions. This position is designed for entry-level to early-career professionals who are building foundational capability across data engineering, business intelligence, data modeling, reporting, and analytics delivery.

Key Responsibilities

• Assist in the design, development, testing, and support of Data and Analytics solutions, including data pipelines, data models, datasets, dashboards, and reports.
• Support ETL and ELT development activities, including data extraction, transformation, loading, mapping, reconciliation, and validation.
• Write and maintain basic to intermediate SQL queries and Python scripts to support data preparation, automation, validation, and reporting needs.
• Support development of Microsoft Power BI reports and dashboards using approved design standards, data models, visuals, slicers, filters, and basic DAX calculations.
• Assist in building Power BI semantic models by understanding source tables, relationships, joins, business grain, measures, dimensions, and reporting requirements.
• Work with data sourced from cloud platforms, databases, and Databricks to support reporting and analytical use cases.
• Participate in requirements discussions with project teams and business stakeholders, documenting reporting needs, data definitions, assumptions, and open questions.
• Support QA and testing activities, including unit testing, report validation, data comparison, UAT support, defect documentation, and issue remediation.
• Help troubleshoot basic data refresh, visualization, access, data quality, and report performance issues, escalating more complex problems to senior team members.
• Maintain clear documentation, including technical notes, data mappings, report logic, test evidence, user guides, and operational support instructions.