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Data Analyst

Evlo AI · Miami, FL

Spotted 5d agoFull-time

Job details

Employment
Full-time
Experience
3+ years
Education
Bachelor's degree
Posted
Oct 25, 2026
Last confirmed open
Oct 26, 2026
Job description

About this role

About The Role

The Data Analyst owns the analytical layer of a fast-scaling product and revenue organization — turning raw event streams, warehouse tables, and operational data into metrics leadership actually acts on.

The role sits between data engineering and business strategy: building reliable semantic layers, designing experiments, and shipping dashboards that answer questions before they're asked.

Key Responsibilities

  • Build and maintain SQL models in Snowflake/BigQuery (dbt preferred), ensuring data quality, documentation, and consistent metric definitions across teams
  • Design and ship dashboards in Looker or Tableau for product, growth, and finance stakeholders — with clear naming conventions and self-serve usability
  • Run A/B test design and analysis: experiment sizing, statistical significance testing, and post-launch readouts with clear business recommendations
  • Partner with data engineers to define ingestion requirements, improve pipeline reliability, and reduce time-to-insight on new data sources
  • Perform deep-dive analyses on retention, funnel conversion, unit economics, and user behavior using SQL and Python
  • Define and instrument KPIs with product managers, owning metric documentation and guarding against metric drift
  • Present findings to leadership with concise written narratives and clear visualizations — not just raw numbers

What We Are Looking For

  • 3–6 years of experience in data analysis, analytics engineering, or a closely related role
  • Expert-level SQL — window functions, CTEs, query optimization — and strong Python for analysis (pandas, NumPy)
  • Hands-on experience with a modern warehouse (Snowflake, BigQuery, Redshift) and BI tools (Looker, Tableau, or Power BI)
  • Track record of owning analytics end-to-end: stakeholder intake, modeling, analysis, and executive communication
  • Solid statistics foundation: hypothesis testing, regression, experiment design, and knowing when not to overfit a conclusion
  • Bachelor's degree in a quantitative field or equivalent practical experience
  • Bonus: dbt experience, event analytics tooling (Amplitude, Mixpanel, Segment), Airflow exposure, or experience in a B2B SaaS environment
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