Business Data Analyst

Evlo AI; Boston (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

Evlo AI in Boston seeks a data analytics engineer who translates raw operational data into trustworthy metrics, dashboards, and insights that leadership and product teams rely on weekly to guide decisions.

You will own the analytical layer in a modern data stack—semantic models, KPI definitions, and experiments—collaborating with data engineers, analytics engineers, data scientists, and stakeholders to shape product and go-to-market strategy, while building scalable dashboards in Looker,

Qualifications

• 3–6 years of experience in data analytics, business intelligence, or analytics engineering.
• Expert-level SQL and hands-on experience with dbt or similar transformation frameworks in a cloud warehouse (Snowflake, BigQuery, Redshift).
• Strong Python skills for data analysis and automation (pandas, matplotlib or equivalent).
• Demonstrated experience building dashboards and semantic models in Looker, Tableau, or Power BI.
• Solid foundation in statistics: hypothesis testing, experiment design, regression, and common analytical pitfalls.
• Bachelor's degree in a quantitative field (statistics, economics, computer science, engineering) or equivalent practical experience.
• Bonus: experience with data catalog tools (Atlan, Monte Carlo), reverse ETL workflows, or owning metric layers in a data mesh environment.

Responsibilities

• Build and maintain core business dashboards in Looker (or Tableau) covering growth, retention, and operational efficiency metrics.
• Write performant SQL models in Snowflake/BigQuery using dbt, ensuring version control, testing, and documentation for the semantic layer.
• Design and analyze A/B tests and quasi-experiments, partnering with data scientists on experiment design and statistical rigor.
• Partner with product, marketing, and finance stakeholders to define KPIs, diagnose metric anomalies, and deliver actionable insights.
• Develop Python-based analyses (pandas, Jupyter) for churn modeling, cohort analysis, and funnel optimization.
• Identify and fix data quality issues upstream in ELT pipelines (Airflow/Fivetran), collaborating with data engineers on root cause resolution.
• Automate recurring reporting workflows, eliminating manual processes and improving self-serve analytics for the organization.

Skills

SQL

dbt

Python

BI dashboards

Statistics

Education

Bachelor's degree (quantitative)

Tools

Snowflake

BigQuery

Redshift

Looker

Tableau

Power BI

Airflow

Fivetran

dbt

Job description

About The Role

The role sits at the intersection of analytics and engineering - translating raw operational data into trustworthy metrics, dashboards, and insights that leadership and product teams use to make decisions weekly.

About The Role

The role sits at the intersection of analytics and engineering - translating raw operational data into trustworthy metrics, dashboards, and insights that leadership and product teams use to make decisions weekly.

You will work within a modern data stack alongside data engineers and analytics engineers, owning the analytical layer: semantic models, KPI definitions, and experiments that directly shape product and go-to-market strategy.

Key Responsibilities

• Build and maintain core business dashboards in Looker (or Tableau) covering growth, retention, and operational efficiency metrics
• Write performant SQL models in Snowflake/BigQuery using dbt, ensuring version control, testing, and documentation for the semantic layer
• Design and analyze A/B tests and quasi-experiments, partnering with data scientists on experiment design and statistical rigor
• Partner with product, marketing, and finance stakeholders to define KPIs, diagnose metric anomalies, and deliver actionable insights
• Develop Python-based analyses (pandas, Jupyter) for churn modeling, cohort analysis, and funnel optimization
• Identify and fix data quality issues upstream in ELT pipelines (Airflow/Fivetran), collaborating with data engineers on root cause resolution
• Automate recurring reporting workflows, eliminating manual processes and improving self-serve analytics for the organization

What We Are Looking For

• 3–6 years of experience in data analytics, business intelligence, or analytics engineering, ideally at a high-growth technology company
• Expert-level SQL and hands-on experience with dbt or similar transformation frameworks in a cloud warehouse (Snowflake, BigQuery, Redshift)
• Strong Python skills for data analysis and automation (pandas, matplotlib or equivalent)
• Demonstrated experience building dashboards and semantic models in Looker, Tableau, or Power BI
• Solid foundation in statistics: hypothesis testing, experiment design, regression, and common analytical pitfalls
• Bachelor's degree in a quantitative field (statistics, economics, computer science, engineering) or equivalent practical experience
• Bonus: experience with data catalog tools (Atlan, Monte Carlo), reverse ETL workflows, or owning metric layers in a data mesh environment