Business Intelligence Engineer, Ring AI Data Management
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.
BASIC QUALIFICATIONS
- Experience analyzing and interpreting data with relational databases
- Experience with writing complex SQL queries
- Experience with data modelling, warehousing and designing ETL pipelines
- Experience using scripting languages Python, Java Script in order to process data for modelling
- Experience with AWS, including Redshift, S3, Athena.
- Experience in statistical and root cause analysis techniques
- Experience with data visualization using Tableau, QuickSight, or similar tools
PREFERRED QUALIFICATIONS
- Proficient in handling big data volumes, composition of advanced SQL and query performance tuning skills.
- Experience in data mining in a business environment with large-scale, complex datasets.
- Experience in workforce performance management or business process automation analysis or system analysis would be a plus.
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