Lead Data Analyst

October 17

Apply Now

Receive Emails with Similar Jobs

The Baldwin Group

WebsiteLinkedInAll Job Openings

Commercial Risk Management • Private Risk Management • Personal Insurance • Employee Benefits • Asset and Income Protection

1001 - 5000

Description

• The Lead Data Analyst is part of the Data and Analytics Organization and is responsible for the design, development, and delivery of actionable insights and data-driven solutions to support strategic decision-making within the organization. • Exemplifying technical excellence and thought leadership. • Responsibilities include designing, developing, and delivering dashboards, reports (using Power BI), and other data-driven solutions that provide actionable insights to stakeholders across the organization. • Providing technical thought leadership, conducting code reviews, technical mentorship, and aiding the BI Manager in the development of data analysts on the team. • Design and lead the development of business intelligence solutions for the organization using Power BI, Power Automate and Power Apps. • Develop and maintain dashboards, reports, prepare data visualizations, and use data to forecast or guide business activity. • Monitor database reporting systems performance, troubleshoot and resolve data related issues. • Identify and implement technical and/or process changes to improve the performance, accuracy, timeliness, and/or efficiency of database, reporting, and dashboard operations.

Requirements

• Bachelor’s degree in related field preferred, equivalent years’ experience considered. • At least seven years of data related or analytical work experience. • Must have experience building BI solutions using Power BI, Power Automate and Power Apps. • Insurance industry experience preferred, but not required. • MS Azure skills preferred including intermediate skills in Data Factory, Synapse Analytics, Power BI or equivalent. • Intermediate to advanced SQL / T-SQL experience. • Ability to grasp database structures and understand the underlying relationships and dependencies. • Comfortable compiling data integration from multiple sources; performing quality control on data sets; identifying and scrutinizing anomalies and/or outliers in the data; ability to manipulate data and complete required analysis.