Manager, Business Intelligence

Playlist

17h

About The Position

As Manager, Business Intelligence, you will lead how Playlist transforms complex product data into trusted, scalable insights—powering both internal decision-making and customer-facing analytics products. You’ll partner closely with Product, Product Analytics, and Engineering to define, build, and operationalize high-quality data models that support a highly customizable product ecosystem. This role sits at the intersection of product analytics, data modeling, and data product development. You’ll own internal product data foundations, enable fast and reliable insight generation, and lead the data layer powering both our external Analytics 2.0 product and internal AI-driven capabilities. You’ll manage and grow a small, high-impact team (2 direct reports with near-term hiring), setting a high bar for data quality, scalability, and business impact.

Requirements

7+ years of experience in business intelligence, analytics, or data-focused roles in a high-growth or product-driven environment
3+ years of experience managing or mentoring analysts, with a track record of building high-performing teams
Strong experience partnering with Product and/or Product Analytics teams, including deep understanding of product metrics, event data, and user behavior analysis
Deep expertise in SQL and data modeling, including designing datasets for both internal analytics and external-facing use cases
Experience working with complex, raw datasets and transforming them into scalable, reliable data models
Experience supporting or building data products (e.g., customer-facing analytics, embedded reporting, APIs)
Familiarity with AI/ML data workflows or strong interest in supporting AI-driven product development
Strong understanding of data quality, governance, and testing best practices
Hands-on experience with modern data stacks, including Snowflake, dbt Cloud, and BI tools such as Looker and Sigma Computing
Ability to balance speed and precision in a fast-moving environment with ambiguous requirements
Excellent communication skills, with the ability to translate complex data into clear insights for both technical and non-technical stakeholders

Responsibilities

Lead the development and maintenance of scalable, high-quality data models that represent our complex, customizable product ecosystem
Transform raw, fragmented product data into clean, reliable datasets used across internal analytics and external products
Establish and enforce best practices for data modeling, testing, and governance across product datasets
Work closely with Product Analytics to enable fast, accurate, and actionable insights on product performance, user behavior, and feature adoption
Align on metric definitions, instrumentation needs, and data availability to ensure consistent and trusted reporting
Support rapid iteration by balancing data quality with speed-to-insight
Own the data layer powering Analytics 2.0, ensuring datasets are accurate, performant, and intuitive for customer consumption
Design and maintain customer-facing data models that balance flexibility with ease of use across a highly configurable product
Partner with Product and Engineering to evolve Analytics 2.0 capabilities and expand reporting functionality
Maintain a high bar for data quality, consistency, and trust in all external-facing datasets
Partner with Product, Engineering, and Data teams to support the development of internal AI use cases (e.g., LLM-powered insights, automation, and decision support tools)
Define and prepare high-quality, well-structured datasets that can be leveraged for AI/ML applications, including prompt-ready and feature-ready data
Ensure data powering AI use cases is accurate, consistent, and aligned with business logic and product definitions
Identify opportunities to leverage AI to improve internal analytics workflows, speed to insight, and data accessibility
Help establish best practices for how BI contributes to AI development, including data preparation, validation, and ongoing monitoring
Lead deep-dive analyses on product performance and key business drivers, translating findings into clear recommendations
Support product and leadership teams with data-informed decision-making and roadmap prioritization
Collaborate with Data Platform and Engineering to improve data pipelines, automation, and overall system reliability
Continuously improve workflows to support a growing data ecosystem and increasing product complexity
Manage, mentor, and develop a team of BI analysts, fostering strong ownership and technical excellence
Hire and onboard additional team members to support expanding scope
Create a clear operating rhythm, prioritization framework, and high-quality execution standards