Business Intelligence Engineer II, Ring Data Science and Engineering

Business Intelligence Engineer II, Ring Data Science and Engineering

We are seeking a Business Intelligence Engineer to build reports and analytics for the Ring Business. You will deliver data‑driven insights on how users interact with Ring Products and sites. You will partner with product teams to understand their data needs, and look for opportunities to utilize GenAI tooling to accelerate time to insights. You will balance competing priorities to deliver actionable insights while building toward long‑term data solutions.

A successful candidate will have strong analytical and technical skills in data analytics and visualization. You will communicate complex data findings clearly to stakeholders and leadership. With your expertise and judgment, you'll make a meaningful impact.

As a Business Intelligence Engineer, you will solve ambiguous problems and implement data‑driven solutions to improve store builder experience and business outcomes. You'll extract, integrate, and analyze critical data to design key performance metrics and indicators that drive strategic decisions.

A typical day offers opportunities to build innovative solutions with large‑scale data systems and solve complex problems that impact strategic decisions across the company.

You'll start by partnering with stakeholders to understand their manual processes and pain points, diving deep to identify root causes. You'll think creatively about technology‑driven solutions that can automate workflows and eliminate inefficiencies.

Your day includes designing and implementing data pipelines, building dashboards that surface meaningful insights, and prioritizing high‑impact projects that deliver maximum value to stakeholders. You'll respond to ad‑hoc requests, troubleshoot reporting issues, and provide technical support to business teams.

• Experience in analyzing and interpreting data with Redshift, Oracle, No
  
  SQL, etc.
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• 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
• Experience with SQL
• Experience in the data/BI space

• Experience with AWS solutions such as EC2, Dynamo
  
  DB, S3, and Redshift
• Experience in data mining, ETL, etc. and using databases in a business environment with large‑scale, complex datasets

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