Data Analyst

Evlo AI; Chicago (IL); On-site; USD 110,000 - 160,000; Full time

Job summary

Evlo AI is seeking an experienced Data Analytics professional to turn raw product, revenue, and operational data into actionable analyses driving roadmap and go-to-market decisions. You will own end-to-end metrics, from defining definitions with stakeholders to building SQL and dbt models that ensure reliable measurements.

You will partner with analytics engineers, data engineers, and business leaders in a modern data stack (Snowflake, dbt, Looker) where your work shapes pricing, product

Qualifications

• 3-6 years of experience in data analytics or BI at a product-driven company
• Expert-level SQL with complex joins, window functions, and large datasets
• Hands-on experience with dbt and cloud data warehouses (Snowflake/BigQuery/Redshift)
• Proficiency in Python or R for ad-hoc analysis and modeling
• Experience with modern BI tools and semantic layer definitions
• Strong communication of technical findings to non-technical stakeholders

Responsibilities

• Own core business metrics end-to-end: define, instrument, validate, and monitor KPIs across product usage, retention, and revenue
• Build and maintain dbt models and SQL transformations in Snowflake
• Design and develop dashboards in Looker or similar BI tools used by leadership
• Run deep-dive analyses (cohorts, funnels, pricing experiments) and present actionable recommendations
• Collaborate with product and growth to translate questions into analytical frameworks
• Identify data quality issues and build automated tests with data engineers

Skills

SQL proficiency

Big data analysis

Data storytelling

Education

Bachelor's degree in a quantitative field

Tools

dbt

Snowflake

Looker

Python or R

Job description

About The Role

The role sits at the center of the company's data ecosystem, turning raw product, revenue, and operational data into analyses that drive roadmap and go-to-market decisions. This is not a dashboard-maintenance position - the analyst owns problems end-to-end, from defining metrics with stakeholders to building the SQL and dbt models that make those metrics reliable.

About The Role

The role sits at the center of the company's data ecosystem, turning raw product, revenue, and operational data into analyses that drive roadmap and go-to-market decisions. This is not a dashboard-maintenance position - the analyst owns problems end-to-end, from defining metrics with stakeholders to building the SQL and dbt models that make those metrics reliable.

You will work closely with analytics engineers, data engineers, and business leaders in a modern data stack environment (Snowflake, dbt, Looker), where your work directly shapes pricing, product prioritization, and growth strategy.

Key Responsibilities

• Own core business metrics end-to-end: define, instrument, validate, and monitor KPIs across product usage, retention, and revenue
• Build and maintain dbt models and SQL transformations in Snowflake, ensuring data quality and consistent metric definitions across the organization
• Design and develop dashboards in Looker (or similar BI tools) that leadership and cross-functional teams actually use to make decisions
• Run deep-dive analyses - cohort retention, funnel analysis, pricing experiments, A/B test evaluation - and present findings with clear recommendations
• Partner with product managers and growth teams to translate ambiguous business questions into rigorous, testable analytical frameworks
• Identify data quality issues upstream, work with data engineers on root causes, and build automated tests to catch regressions early
• Contribute to the team's documentation, metric dictionaries, and analytical best practices

What We Are Looking For

• 3-6 years of experience in data analytics, business intelligence, or a comparable analytical role at a product-driven company
• Expert-level SQL - complex joins, window functions, CTEs, performance tuning - and the ability to work with large, messy datasets independently
• Hands-on experience with dbt (or similar transformation tooling) and a cloud data warehouse such as Snowflake, BigQuery, or Redshift
• Proficiency in Python or R for ad-hoc analysis, statistical testing, and lightweight modeling; comfort with pandas is expected
• Experience with a modern BI tool (Looker, Tableau, Power BI) including semantic layer or metric definition work
• Track record of communicating technical findings to non-technical stakeholders and influencing decisions with data
• Bachelor's degree in a quantitative field (statistics, economics, CS, engineering) or equivalent practical experience. Bonus: experience with experimentation platforms and causal inference methods, exposure to Airflow or other orchestrators, or prior work in a B2B SaaS environment