Business Data Analyst — Chicago, IL

About The Role

The role sits at the intersection of data infrastructure and business strategy — turning pipelines, warehouse models, and product data into decisions that shape roadmap and revenue.

The analyst owns dashboards, experimentation analysis, and self-serve data models used across operations, growth, and finance, partnering directly with senior leaders to define the metrics that actually get used.

Key Responsibilities

• Own and evolve core business metrics — activation, retention, revenue attribution — defining clear metric logic and documenting it in a shared semantic layer

• Build and maintain dbt models in Snowflake (or similar), ensuring data correctness, freshness, and clear lineage across transformation layers

• Design and ship dashboards in Looker or Tableau that executive teams rely on weekly, with attention to performance, readability, and version control

• Analyze experiments and product funnels using SQL and Python, translating statistical results into concrete recommendations for product and growth teams

• Partner with data engineers to improve pipeline reliability, backfill strategy, and data quality tests using dbt tests and custom monitoring

• Serve as the analytics point of contact for 2–3 business domains, running stakeholder intake, prioritization, and delivery of analyses

• Investigate anomalies in business data proactively — identifying instrumentation gaps, upstream failures, or genuine shifts in user behavior

What We Are Looking For

• 3–6 years of experience in data analytics, analytics engineering, or a comparable data-focused role at a product or technology company

• Expert-level SQL: window functions, CTEs, query optimization, and working with large warehouse datasets (Snowflake, BigQuery, or Redshift)

• Hands-on experience with dbt or a similar transformation framework, including testing, documentation, and model layering

• Working proficiency in Python for analysis (pandas, NumPy) and basic statistical methods — significance testing, confidence intervals, regression

• Track record of building dashboards in Looker, Tableau, or Power BI that senior stakeholders actually use to make decisions

• Bachelor's degree in a quantitative field (statistics, economics, computer science, engineering) or equivalent practical experience

• Bonus: experience with experimentation platforms (Amplitude, LaunchDarkly, internal A/B tools), reverse ETL tools (Hightouch, Census), or ownership of a metrics/semantic layer