AI & BI Engineer II

At Niagara, we're looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water.

Consider applying here, if you want to:

* Work in an entrepreneurial and dynamic environment with a chance to make an impact.

* Develop lasting relationships with great people.

* Have the opportunity to build a satisfying career.

We offer competitive compensation and benefits packages for our Team Members.

AI & BI Engineer II

The Enterprise AI & BI Engineer II is a mid-level technical role responsible for designing, developing, and delivering business intelligence solutions, analytics data models, and AI-enabled analytics capabilities. This role independently contributes to the organization's analytics and decision intelligence ecosystem by building scalable data assets, dashboards, and automation solutions that support business decision-making. The Engineer II applies strong foundational knowledge in data modeling, business intelligence, and applied AI to deliver high-quality analytics solutions.

This role begins to take ownership of components within the data and analytics platform while contributing to the adoption of AI-driven insights and intelligent automation across the enterprise.

Essential Functions

* Design, build, and maintain business intelligence dashboards, reports, and data visualizations aligned with business requirements

* Develop and manage curated datasets, semantic layers, and data marts to support consistent and scalable analytics

* Translate business requirements into well-structured analytics solutions with clear logic and performance considerations

* Optimize BI solutions for usability, performance, and scalability

* Design and implement analytics data models using dimensional modeling and ELT best practices

* Build and maintain data transformations and pipelines that support reporting and analytics use cases

* Partner with data engineering teams to ensure high-quality, reliable data pipelines for analytics consumption

* Ensure consistency of business logic, metrics, and definitions across analytics assets

* Develop and support AI-assisted analytics capabilities such as predictive models, automated insights, and natural language data interactions

* Apply basic machine learning techniques or integrate pre-built models into analytics workflows

* Support automation of reporting, data validation, and insight generation processes

* Collaborate with data science teams to operationalize model outputs into dashboards and business workflows

* Apply data quality validation, testing, and monitoring practices to ensure reliable analytics outputs

* Support implementation of data governance standards, including documentation, metadata, and metric definitions

* Contribute to the development of reusable data assets and standardized reporting frameworks

* Collaborate with business stakeholders to gather requirements and deliver analytics solutions that meet business needs

* Participate actively in agile delivery processes including sprint planning, backlog grooming, and demos

* Work cross-functionally with data engineers, analysts, and AI teams to deliver integrated solutions

* Continuously improve technical skills in BI tools, data engineering, and applied AI/ML

* Identify opportunities to improve existing analytics solutions through automation, optimization, or AI enhancements

* Begin contributing to team best practices and knowledge sharing

Qualifications

* Minimum Qualifications:

* 3 - 5 years of experience in business intelligence, data analytics, AI, or related fields (internships or academic experience included)

* Strong understanding of designing enterprise analytics data models, semantic layers, or BI platforms.

* experience may include a combination of work experience and education

* Preferred Qualifications:

* 5 - 7 years of experience in business intelligence, data analytics, AI, or related fields (internships or academic experience included)

* Strong Skillset in data modeling concepts (e.g., star schema, dimensional modeling)

* Strong familiarity with Python, R, or other programming languages

* Strong exposure to AI/ML concepts or tools (e.g., basic modeling, notebooks, or AI-assisted tools)

* Familiarity with cloud data platforms or modern data tools

* experience may include a combination of work experience and education

Competencies

* Strong experience building scalable dashboards and reports

* Understanding of data visualization best practices and user experience

* Ability to independently deliver analytics solutions from requirements to deployment

* Solid understanding of data pipelines, transformations, and data warehousing concepts

* Experience implementing ELT patterns and optimizing data models

* Understanding of performance tuning and data optimization

* Basic hands-on experience with AI/ML integration or predictive analytics

* Understanding of how to operationalize model outputs into business workflows

* Familiarity with AI-assisted analytics tools and automation

*…