Business Intel Engineer II, Ring/Blink Customer Service Engineering and Insights

We are seeking a Business Intelligence Engineer II to join our Customer Service Engineering Services team at Ring & Blink. This role focuses on delivering the next generation of reporting and analytics for Customer Service (CS): owning end-to-end delivery of Amazon QuickSight dashboards, leading the migration of legacy Tableau assets to QuickSight, and inventing AI-enabled analytics experiences on top of our newly consolidated data platform.

You will build production analytics solutions in Amazon QuickSight, partner directly with business stakeholders to shape reporting strategy, and drive adoption of AI-assisted and agentic patterns that move us beyond traditional static dashboards. This is a delivery-and-invention role: you own outcomes end-to-end and set the technical bar for the reporting you own.

Role Context

Customer Service data has been migrated to a dedicated Amazon Redshift cluster (Radius). Core designs and the initial migration are in place. This role focuses on the next phase: retiring the legacy Tableau footprint by rebuilding on QuickSight and Radius, standing up new reporting for business partners, and introducing AI-powered analytics on the modernized platform.

Key job responsibilities

• Deliver Amazon QuickSight dashboards end-to-end - requirements, data modeling, Structured Query Language (SQL), visualization, publishing, iteration.
• Lead Tableau to QuickSight migration workstreams: audit, redesign on Radius, rebuild, sunset legacy assets.
• Partner directly with Customer Service Operations, Workforce Management, Voice of Customer, and Tech leadership on requirements and metric definitions.
• Write and maintain production SQL against Amazon Redshift for modeling, reporting, ad-hoc analysis, and data validation.
• Build Python tooling for parsing, backfills, validation, and reporting automation.
• Contribute to AI-powered analytics solutions using large language models and agentic patterns - self-service question-answering, automated insights, analyst copilots.
• Own data quality, dashboard performance, documentation, and stakeholder satisfaction for the reports you deliver.

A day in the life

A typical week blends delivery, invention, and partnership. You sync with the Data and Analytics team on active dashboards and migration progress, meet a stakeholder to turn a vague reporting ask into a clear metric and plan, and spend focused time in QuickSight writing SQL against Radius and shaping datasets. You redesign a legacy Tableau workbook for QuickSight, prototype an AI-assisted analytics feature such as a natural-language question-answering interface, review a teammates work, and trace an unexpected number on an executive dashboard back through the pipeline to land a fix.

About the team

The Ring/Blink Customer Service Engineering and Insights team owns the technical side of customer service, the systems, CRM platforms, contact center tooling, integrations, data warehouse, and analytics that customer service runs on. We bring together Salesforce developers, SDEs, SAs, Business Intelligence Engineers, and Data Engineers to build and operate that stack. This role sits on the Customer Service Data and Analytics sub-team, which owns the data warehouse (Radius on Amazon Redshift), the analytics stack (QuickSight, with Tableau retiring), and the pipelines feeding both. Our culture emphasizes rapid prototyping, problem-solving, and AI-assisted development.- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience

• 1+ years of SQL, ETL or Oracle experience
• 1+ years of processing large, multi-dimensional datasets from multiple sources experience
• 1+ years of performing statistical analysis experience
• 1+ years of developing automated reporting experience
• Bachelors degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling