Senior Business Intelligence Engineer, Amazon Ads Machine Learning

$117,300 - $202,800/Yr

Amazon - Seattle, WA

Full-time - Mid Level

Seattle, WA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Senior Business Intelligence Engineer role at Amazon Ads Machine Learning involves building and driving data analytics solutions to support the Ad Catalyst team. This position focuses on leveraging machine learning insights to enhance advertising strategies and outcomes for clients. The engineer will collaborate with cross-functional teams to translate business needs into actionable data insights, ensuring high-quality BI solutions and mentoring junior team members.

Responsibilities

• Partner closely with product managers, engineers, and scientists to understand business requirements and user needs.
• Drive the organization-level data analytics solution as the single-threaded owner of the BI program.
• Design and develop robust, highly performant BI solutions using the latest AWS technologies.
• Create dashboards and strategic studies to inform the team and senior leadership of business-critical revenue and advertiser impact opportunities.
• Guide the implementation of best practices in BI, optimizing performance and ensuring data quality and governance.
• Mentor and coach junior BI team members, sharing expertise and helping them grow their skills.

Requirements

• 5+ years of professional or military experience.
• Experience in scripting for automation (e.g. Python) and advanced SQL skills.
• Experience with data visualization using Tableau, Quicksight, or similar tools.
• Experience managing, analyzing, and communicating results to senior leadership.
• Experience working directly with business stakeholders to translate between data and business needs.
• Demonstrated experience in leading cross-functional teams and driving BI initiatives from ideation to implementation.

Nice-to-haves

• Experience with AWS technologies.
• Master's degree in statistics, data science, or an equivalent quantitative field.
• Knowledge of data warehousing and data modeling.
• Experience with theory and practice of information retrieval, data science, machine learning, and data mining.
• Familiarity with data engineering concepts, such as data pipelines, data quality, and performance optimization.

Benefits

• Medical insurance
• Financial benefits
• Equity options
• Sign-on payments
• Comprehensive employee benefits package