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Business Intelligence Engineer, Ring AI Data Management

Amazon

Amazon

Software Engineering, Operations, Data Science
Gdańsk, Poland · Gdynia, Poland
Posted 6+ months ago

DESCRIPTION

Business Intelligence Engineer at Ring AI Data Management to support the team in creating insights, dashboards and reports that help leadership to make data-driven decisions in the area of business process automation and workforce performance management. This person will create self-service dashboards and work closely with data engineers on reporting automation.

Key job responsibilities
- Use data to create insights to Ring AI Data Management leaders which include detailed business analysis, outlining problems, opportunities and solutions recommendations.
- Write compelling narratives to share data stories to stakeholders and equip them to make informed decisions and future plans.
- Provide data for weekly and monthly business reviews, which includes business process optimisation indicators, workforce performance indicators, capacity planning recommendations.
- Take a proactive approach to defining new metrics, reports, and dashboards.
- Develop self-service dashboards using Tableau, Quicksight.
- Browse available data sources in order to understand the business processes and enhance analytics events logging.
- Work closely with the data engineering team to design, execute and maintain reporting modules, lead automation of recurring reports.

A day in the life
The successful candidate will be on the lookout for ways to optimize the information flow process, superior communications skills and the ability to deliver analysis in a clear and actionable format, analytical ability and technical skills to come up with data-driven proposals on ways how to optimize employee’s efficiency.

About the team
The Ring AI Data Management team owns tools and services for Ring's growing ML-based Research & Development needs. The portfolio of services managed by the team comprises of centralized R&D data ingestion, aggregation and building standardized data models for the performance management. We collaborate in teams dedicated to customer needs. We lean towards bias for action and quick data-driven decision making.