Business Intelligence Manager

Double Good•Chicago, IL

5h•$108,000 - $155,000•Hybrid

About The Position

Double Good is a leading fundraising app and technology company that helps youth organizations raise funds by selling popcorn. The company is experiencing significant growth and is looking for a Manager of BI to join their Data team. This role is hybrid, requiring 3 days onsite per week at their Elmhurst or downtown Chicago location. The Manager of BI will lead the BI team towards a vision where business users have access to certified Looker dashboards and AI-generated summaries every Monday. This leader will define the 2-year BI strategy and roadmap to achieve this goal. The role reports to the VP of Data & Analytics and leads a team of 2-3 BI Analysts and BI & Analytics Engineers. The team is responsible for the consumption layer, including KPI definitions, certified Looker dashboards, self-service adoption, and insights. This is a player-coach role, involving strategy definition, priority setting, team development, and hands-on work in Looker and SQL.

Requirements

5+ years in business intelligence, analytics, or analytics engineering with demonstrated business impact, including ownership of a reporting ecosystem and KPI framework used by senior leaders.
2+ years managing analysts or analytics engineers with employee development responsibility; strong team-lead experience considered.
Deep Looker experience building and governing production-grade, certified dashboards, with LookML fluency sufficient to review an Explore and write a precise specification.
Expert SQL with working knowledge of dbt and a modern cloud data warehouse (Snowflake, BigQuery, Redshift, or Databricks).
Track record of metric definitions and data-quality standards that held across teams.
Demonstrated ability to collaborate with and influence cross-functional stakeholders through the executive level, verbally and in writing.
Comfort operating in a fast-paced, ambiguous environment.
Experience with AI/GenAI-enabled analytics and a clear point of view on what makes a certified metric usable by an LLM or agent.
Bachelor's degree in business analytics, information systems, computer science, statistics, economics, or a related field, or equivalent experience.

Nice To Haves

Experience in a direct-to-consumer e-commerce or CPG business.
Hands-on delivery of AI-generated summaries or natural-language Q&A on governed BI data (for example, Claude with Looker and Snowflake).
Experience building self-service analytics platforms or delivering BI outputs as inputs to forecasting, planning, finance close, or experimentation platforms.
Prior hands-on dbt or LookML development; Python and Git-based workflows.
Growth and lifecycle analytics (acquisition, repeat, referral), A/B testing, or experimentation frameworks.
Finance and operations metric literacy: revenue recognition, COGS, contribution margin, forecast accuracy, on-time shipment, unit cost.
Looker or dbt certification, or a CDMP or CBIP data-management credential.

Responsibilities

Own the BI roadmap: a prioritized quarterly plan, tied to the four business impacts, that moves every function from reactive reporting toward certified dashboards and AI-generated summaries.
Lead, mentor, and grow a high-performing team of 2-3: provide technical guidance, career development, and clear goals for BI Analysts and BI & Analytics Engineers.
Own the end-to-end BI lifecycle: standardized intake, requirements definition, and delivery from prototype to production-grade dashboards that are accurate, repeatable, and scalable.
Specify what the semantic layer must deliver: metric definitions, grain, dimensions, and acceptance tests for Analytics Engineering, replacing one-off solutions with shared, reusable metrics; BI signs off before certification.
Champion data governance, metric consistency, and quality assurance: one definition per metric, a named owner, tests, documentation, and a change process, so leadership works from a single source of truth.
Drive certification and business adoption: define "certified," retire content that does not qualify, and grow Looker adoption through Explores, training, and usage tracking.
Make BI AI-ready: establish the naming, documentation, and business-context standards that let AI read certified metrics as reliably as a person, and own the quality of AI-generated summaries.
Translate complex business questions into actionable intelligence: partner with functional leaders to define the metrics behind each decision, deliver concise written recommendations that change outcomes, and manage BI delivery across Data Engineering, Analytics Engineering, and Product.