We're looking for a Business Intelligence Engineer to partner with engineering and product teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights
You are not simply a dashboard developer. You’ll build trusted semantic layers and operational reporting, enable self‑serve analytics, and partner with business owners translate ambiguous questions into structured, measurable problems and roadmaps. Your’ll partner directly with business owners and data partners and your work will be used from org to the C‑suite.
Successful candidates will have:
A passion for creating accessible and intuitive data models. Knowledge of data warehouse modeling best practices and tradeoffs (dimensional data modeling, Kimball, Inmon, etc.).
An obsession with data quality and cleanliness.
A knack for crisp, self‑serve data products (such as dashboards) that tell a story and drive action
A drive to make partners successful—their problems are your problems.
- Partner Strategically: Collaborate with Product, Marketing, Sales, and Engineering teams to understand their goals and challenges. Your work will directly influence decision-making across the organization.
- Build Solutions: Design, develop, and maintain reliable data pipelines and models that turn raw data into meaningful insights. Your work will simplify complex concepts into user-friendly dashboards and visualizations.
- Enable self‑serve: build and maintain executive and team dashboards and data products that reduce ad‑hoc and increase decision speed.
- Drive Impact: Identify trends, diagnose problems, and craft solutions using metrics, reporting tools, and predictive models.
- Ensure Quality: Maintain high standards for data governance, privacy, and security while ensuring data quality and reliability.
- Communicate Insights: Translate business needs into technical requirements and explain results to non‑technical audiences, empowering stakeholders at all levels to take action.
- Prioritization: Understand what matters most and prioritize ruthlessly
- Proficiency in SQL with hands-on experience building and optimizing data pipelines.
- Knowledge of data modeling best practices (e.g., dimensional modeling).
- Experience with BI tools such as Tableau, Looker, or PowerBI.
- Analytical Mindset: Strong problem-solving skills and the ability to identify key trends in complex datasets.
- Collaboration Skills: A natural communicator who can translate business needs into technical requirements and technical results into actionable business insights.
- 6+ years of experience in analytics, data engineering, or a similar field.
- Proven track record of delivering data-driven projects that drive meaningful results.
- Familiarity with cloud environments like Snowflake or Databricks is a plus.
- Bachelor’s degree in a quantitative field like Computer Science, Engineering, Statistics, or Economics. Master’s degree is a plus.
- Product analytics experience in a SAAS company
- Experience with predictive modeling, Machine Learning, and A/B Testing methods
