Staff Business Intelligence Analyst

Prodege•El Segundo, CA

12h

About The Position

Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today! This is a role for someone who enjoys building more than dashboards. We're looking for a Staff Business Intelligence Analyst to help build the next generation of Business Intelligence at Prodege. This is a deeply hands-on engineering role where you'll transform complex data into trusted reporting, scalable analytics models, and reusable data products that enable better decisions across the business. You'll help build the analytics foundation that powers Product, Marketing, Finance, Customer Experience, Publisher Operations, Performance Marketing, and executive reporting. Working alongside Data Engineering, Analytics, and Machine Learning, you'll create reliable datasets, modern semantic models, and self-service reporting solutions that improve how the company uses data every day. You'll work in a modern cloud analytics environment built around Snowflake, dbt, and Sigma while contributing to an AI-first engineering culture that values automation, quality, and continuous improvement. This role focuses on delivering high-quality analytics solutions rather than defining long-term BI architecture or enterprise reporting strategy.

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