Business Intelligence Engineer, IT PnD Data and Analytics

Business Intelligence Engineer, IT PnD Data and Analytics

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.
This 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.

BASIC QUALIFICATIONS

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience writing complex SQL queries
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling.

PREFERRED QUALIFICATIONS

- Experience in the data/BI space
- Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.