AI & BI Engineer II

Niagara Bottling•Diamond Bar, CA

8d•$100,464 - $145,673

About The Position

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.

Requirements

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

Nice To Haves

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
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
Strong problem-solving and analytical thinking
Ability to work independently with minimal supervision
Effective communication with both technical and business stakeholders
Strong attention to detail and commitment to data quality
Power BI, Tableau, or enterprise BI platform certifications, Cloud Data Platform certifications (AWS, Azure, GCP, Snowflake, Databricks), AI / Machine Learning or Advanced Analytics certifications.

Responsibilities

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

Benefits

Paid Time Off for holidays, sick time, and vacation time
Paid parental and caregiver leaves
Medical, including virtual care options
Dental
Vision
401(k) with company match
Health Savings Account with company match
Flexible Spending Accounts
Expanded mental wellbeing benefits including free counseling sessions for all team members and household family members
Family Building Benefits including enhanced fertility benefits for IVF and fertility preservation plus adoption, surrogacy, and Doula reimbursements
Income protection including Life and AD&D, short and long-term disability, critical illness and an accident plan
Special discount programs including pet plans, pre-paid legal services, identity theft, car rental, airport parking
Tuition reimbursement, college savings plan and scholarship opportunities