Business Data Analyst

Evlo AI; San Francisco (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Evlo AI is seeking a data analytics professional to translate raw operational data into durable analytics assets. You will work with product, growth, and finance teams, partnering with data engineers to build reliable datasets and impactful dashboards.

The role focuses on cohort retention, A/B test evaluation, pricing and unit economics, and proactive analytics across business units. A strong Python and SQL background is essential.

Qualifications

• 3–6 years of experience in data analytics, BI, or analytics engineering at product-driven tech companies.
• Expert-level SQL writing complex, performant queries against large datasets.
• Hands-on experience with dbt or similar transformation tooling along with version control/CI workflows.
• Strong Python (pandas, numpy) for analysis and automation.
• Experience building executive dashboards and communicating findings to non-technical stakeholders.
• Bachelor's degree in a quantitative field or equivalent practical experience.

Responsibilities

• Build and maintain SQL models in Snowflake and dbt with accurate data across core domains.
• Design and deliver Looker/Tableau dashboards tracking product engagement, revenue, and funnel performance.
• Own end-to-end analyses from hypothesis framing to stakeholder readouts.
• Collaborate with data engineers to define metrics, schemas, and data quality checks.
• Run experiments with proper design, statistical significance, and clear results communication.
• Automate recurring reporting and ad-hoc workflows in Python to reduce manual work.

Skills

Executive communication

Stakeholder management

Analytical thinking

Problem solving

Education

Bachelor's degree in a quantitative field

Tools

SQL

dbt

Python

Looker

Tableau

Snowflake

BigQuery

Redshift

Job description

About The Role

The role sits at the intersection of data infrastructure and business decision-making, translating raw operational data into models, dashboards, and analyses that leadership actually uses to steer the company.

About The Role

The role sits at the intersection of data infrastructure and business decision-making, translating raw operational data into models, dashboards, and analyses that leadership actually uses to steer the company.

The analyst will work directly with product, growth, and finance teams while partnering closely with data engineers to build reliable, well-modeled datasets - not just one-off queries, but durable analytics assets.

Key Responsibilities

• Build and maintain SQL models in Snowflake and dbt, ensuring data accuracy, freshness, and documentation across core business domains
• Design and deliver dashboards in Looker (or Tableau) that track product engagement, revenue, and funnel performance for stakeholders at all levels
• Own end-to-end analyses - cohort retention, A/B test evaluation, pricing and unit economics - from hypothesis framing through stakeholder readout
• Partner with data engineers to define metrics, contract schemas, and data quality checks in the warehouse
• Run and interpret experiments, including proper test design, statistical significance evaluation, and clear communication of results and caveats
• Automate recurring reporting and ad-hoc request workflows in Python, reducing manual analysis time across the team
• Act as the analytics point of contact for one or more business units, proactively identifying questions the data can answer before they're asked

What We Are Looking For

• 3–6 years of experience in data analytics, business intelligence, or analytics engineering at product-driven technology companies
• Expert-level SQL with demonstrated ability to write complex, performant queries against large warehouse datasets (Snowflake, BigQuery, or Redshift)
• Hands-on experience with dbt or similar transformation tooling, including version control and CI workflows
• Strong proficiency in Python (pandas, numpy) for analysis, prototyping, and automation
• Track record of building executive-facing dashboards and communicating quantitative findings to non-technical stakeholders
• Bachelor's degree in a quantitative field (statistics, economics, computer science, engineering) or equivalent practical experience
• Bonus: experience with A/B testing platforms (GrowthBook, Eppo, Amplitude Experiment), LookML development, or building lightweight data apps in Streamlit