IT PnD Data and Analytics is seeking a Business Intelligence Engineer to join our BI team.

As a Business Intelligence Engineer with our team, you will be working in a large, complex and dynamic, data-driven environment. You will be responsible for developing automated metrics that provide relevant insight to organizational leaders, building and maintaining dashboards, and performing complex data analytics.

This position requires the candidate to develop a deep understanding of the organization and key goals, earn trust with senior leadership, influence without authority, and provide relevant data insights.
To succeed, you must have the ability to engage deeply with diverse and talented business partners, earn trust using facts and data, and advise and influence decisions of senior business leaders through effective verbal and written communication.
The candidate must possess excellent analytical skills, project management experience, and a track record of delivering results in a complex and ambiguous environment.

Key job responsibilities
Perform complex business analysis to help drive organizational decision-making
Complete root cause analysis and provide recommendations to senior leadership to address opportunities
Develop automated metrics that will give senior business leaders insight into the performance of their respective teams and the organization as a whole
Develop and maintain Tableau dashboards
Develop key metrics and shared goals that determine success for a particular area
Take on shared ownership of the weekly organizational metrics scorecard

A day in the life
A day in the life of a BI engineer at IT PnD involves building large-scale reporting solutions using tools like Tableau and QuickSight. The day typically starts with a team stand-up to align on priorities, followed by deep work on developing and refining data transformation, building reports and automating processes. Collaboration with data scientists, analysts, and stakeholders is key to ensure the delivery of right metrics. The day ends with monitoring, code reviews, and documenting progress, all while keeping scalability, efficiency, and Amazon’s high standards for data quality in mind.