Analytics & Data Engineering (Lead or Head)

ABOUT DUALENTRY Founded in 2024, DualEntry is one of the world’s fastest-growing AI startups. At DualEntry, the future of finance is being written today. ERP is one of the largest fintech markets in the world ($220,000,000,000+). Yet, tens of thousands of companies are still using on-premise systems, and the industry has not seen new entrants in more than 30 years. Our AI-native ERP lets accounting teams achieve more in less time. $5M-ARR businesses to NYSE-listed companies trust DualEntry to automate away manual data entry work with AI. We’re finally making the one-person finance team a reality and putting the pain of legacy ERPs from the 1990’s in the past. We operate with urgency and ownership. We move fast. WHY THIS ROLE MATTERS NOW Since starting 18 months ago, we’ve raised $100,000,0000+ from world-class investors such as Lightspeed Venture Partners, Khosla Ventures, Contrary Ventures and Google Ventures, as well as more than 20 angel investors who’ve built, scaled, and exited some of the most impactful companies of the last decade. We got there by moving incredibly fast and hiring an exceptionally sharp, hard-working and deeply committed team from leading tech and accounting companies - Ramp, Meta, Microsoft, Lyft, PwC, Deloitte, J.P. Morgan, Bloomberg, Sage, Xero and Intuit. And some of us don't have a fancy logo on our resume and are here for a shot to prove ourselves. We’re a small team, growing fast with huge momentum - join early. As our Lead Analytics & Data Engineer you’ll drive both data infrastructure and data insights across product, engineering, GTM and marketing from the ground up. This is an intense, hands-on data engineering role with full ownership across all DualEntry teams. We expect you to push for excellence and raise the bar. This is an intense, hands-on Engineer role with full ownership. We expect you to push for excellence and raise the bar. 📍 Location: New York City HQ, 7 World Trade Center WHERE YOU'LL CREATE IMPACT - You have maximum drive to stand up a Data & Analytics function from the ground up. You’ll work with different leaders and pods to create the right KPIs and insights across the entire team. - Full stack analytics engineering development, building models to consume, transform, and expose data internally and externally - Work with closely with different teams to capture, move, store, and transform raw data into highly actionable insights - Collaborate with product, engineering, data and design teams to develop prioritized product roadmaps and measure success - Follow through to turn those insights into action - Set up data processes, tools, and systems that will allow us to make better decisions in a scalable way - Drive a culture of experimental design, testing agenda and best practices with maximum pace, ownership and follow-through WHAT SETS YOU UP FOR SUCCESS - Hardcore work ethic and high agency - Bachelor’s degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields with a minimum of 5 years of industry experience as a Data Scientist - Hands-on experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hex / Hightouch or equivalents) - Hands-on experience with data orchestration platforms (Airflow, Dagster, Prefect) - Hands-on experience with BI tools (preferably Retool, Looker, Mode, Tableau or equivalent) and experience distributing data insights via reports and dashboards - Strong python experience (numpy, pandas, sklearn, etc.) across exploratory data analysis, predictive modeling, and applications of ML techniques to marketing-specific problems - Strong knowledge of SQL (preferably Snowflake, BigQuery, or Redshift) and how to write efficient SQL queries - Proven track record of shipping improvements with engineering, product and GTM organizations - Strong perspective on data science engineering development cycle (data modeling, version control, documentation + testing, best practices for code...