Data Analyst

  • Closed
  • US Company | Micro ( employees)
  • LATAM (100% remote)
  • 3+ years
  • Long-term · 40h/week
  • Finance
  • Full Remote

Required skills

  • SQL
  • Python
  • AWS
  • Apache Airflow
  • ETL
  • zapier
  • dbt
  • Azure
  • HubSpot
  • Excel

Requirements

Must-haves

  • 3+ years of data analytics experience
  • Experience with Python
  • Experience with SQL
  • Experience with ETL pipelines
  • Experience with Apache Airflow
  • Experience with dbt
  • Experience owning entire data lifecycles independently (from data cleaning and pipeline engineering to analytics extraction and executive)
  • Experience building and presenting dashboards, systems, or workflows
  • Exposure with cloud data architectures (AWS, Azure)
  • Experience with automation tools (Zapier, Retool) and CRMs (HubSpot)
  • Proficiency with spreadsheet tools (Excel, Google Sheets) and financial data
  • Ability to debug, triage, and solve problems across complex environments
  • Ability to work with messy, real-world operational data with strong attention to detail
  • Strong communication skills in both spoken and written English

Nice-to-haves

  • Startup experience
  • Experience in fintech or high-growth environments
  • Familiarity with Fivetran, Snowflake, and BigQuery
  • Bachelor's Degree in Computer Engineering, Computer Science, or equivalent

What you will work on

  • Build and maintain core data systems across growth, revenue, and operations, including reporting, CRM/HubSpot, and analytics infrastructure
  • Design reliable data pipelines with documented, tested, easy-to-use source-of-truth tables
  • Catch data quality issues early through validation and monitoring
  • Define and track core company metrics so teams can trust and use dashboards daily
  • Partner directly with founders to monitor operational processes and track SLAs across onboarding, support, and billing
  • Streamline manual processes and reduce spreadsheet-based, manual reporting workflows across billing, revenue operations, onboarding, and customer support
  • Improve data quality and support scalable workflows across cross-functional teams
  • Deliver faster answers to business questions across the company