Staff Business Intelligence Analyst

Prodege•El Segundo, CA

2d•$160,000 - $180,000

About The Position

Prodege is seeking a Staff Business Intelligence Analyst to build the next generation of Business Intelligence. This is a hands-on engineering role focused on transforming complex data into trusted reporting, scalable analytics models, and reusable data products. The analyst will help build the analytics foundation for various departments including Product, Marketing, Finance, Customer Experience, Publisher Operations, Performance Marketing, and executive reporting. Working collaboratively with Data Engineering, Analytics, and Machine Learning teams, the role involves creating reliable datasets, modern semantic models, and self-service reporting solutions within a cloud analytics environment using Snowflake, dbt, and Sigma, fostering an AI-first engineering culture. This role emphasizes delivering high-quality analytics solutions rather than defining long-term BI architecture or enterprise reporting strategy. Key responsibilities include owning trusted analytics datasets, modern analytics data models, dashboards, reporting products, and self-service analytics experiences. The position also involves implementing KPI definitions, ensuring reliable reporting through testing and documentation, and fostering cross-functional partnerships. Continuous improvement of BI engineering practices and AI-assisted development workflows is also a focus.

Requirements

Bachelor's degree in Computer Science, Engineering, Analytics, a quantitative discipline, or equivalent practical experience
Four or more (4+) years of experience in Business Intelligence, Analytics Engineering, Data Analytics, or a related field
Strong SQL skills with experience writing and optimizing complex analytical queries
Hands-on experience with Snowflake or another modern cloud data warehouse
Experience using dbt or similar analytics engineering frameworks
Experience building dashboards and reports using Sigma, Tableau, Looker, Power BI, or comparable BI platforms
Experience in AdTech, Performance Marketing, MarTech, marketplaces, or consumer internet businesses
Strong understanding of dimensional modeling and analytics engineering best practices
Experience developing reusable datasets and scalable reporting solutions
Understanding of KPI implementation, reporting consistency, and trusted business metrics
Strong analytical and problem-solving skills
Experience partnering with cross-functional stakeholders to gather requirements and deliver analytics solutions
Excellent communication skills with the ability to explain technical concepts to non-technical audiences
Experience using AI-assisted development tools to improve SQL development, documentation, or reporting workflows
Ability to manage multiple priorities in a fast-paced environment

Nice To Haves

Experience supporting experimentation platforms, A/B testing, or product analytics
Familiarity with Iceberg or modern lakehouse technologies
Experience improving BI performance, query optimization, and cost efficiency
Experience implementing data quality testing and analytics engineering best practices
Exposure to semantic modeling, reporting governance, and analytics documentation
Experience mentoring junior BI engineers or analysts
Familiarity with AI-first analytics workflows and modern BI engineering practices

Responsibilities

Design, build, and maintain dashboards, reports, and analytics products that support business decision-making
Develop and maintain analytics data models using dbt and Snowflake
Build trusted datasets and reusable reporting assets that enable scalable self-service analytics
Partner with Product, Marketing, Finance, Analytics, and business stakeholders to translate reporting needs into scalable BI solutions
Implement KPI definitions and reporting standards established across the organization
Optimize SQL queries, analytics models, and reporting performance
Validate data quality through testing, monitoring, and documentation
Support executive reporting and operational dashboards
Collaborate with Data Engineering to improve data pipelines and data availability
Troubleshoot reporting issues and continuously improve platform reliability
Contribute to analytics engineering best practices including testing, documentation, version control, and code reviews
Use AI-assisted development tools to improve SQL development, documentation, reporting workflows, and analytics productivity
Mentor junior BI engineers and analytics engineers while sharing technical knowledge across the team