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.
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 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 (EST)
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
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 codebase development)
Familiarity with B2B enterprise sales cycle metrics and processes
Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions
Experience at a high-growth startup
Pragmatic: you like to move forward and make decisions based in reality (not theory). We don't debate if Cassandra has the most theoretical scalability -- we use Postgres until it breaks
Hard working: 'You can work long, hard, or smart, but [here] you can't choose two out of three" - Jeff Bezos. We wrote this job post during the weekend
Curious: you love to learn, are highly curious about new frameworks and solutions to engineering problems
Fast-moving: you deploy daily, iterate quickly, and never wait for permission
Significant equity ownership in one of the top AI companies in the world
You’re joining early and will grow with DualEntry
Your feedback shapes the product directly
High-speed culture
High-trust environment with high expectations
Ambitious mission - ERP is one of the largest B2B software markets in the world ($220bn per year), this is a once in a lifetime opportunity to build the next generation ERP in an industry that has not seen new entrants in 30+ years
Equity: $45,000+ USD
Base Salary: $150,000 – $220,000 USD
Contract type: B2B
Remote-first team - the fastest team you will have ever worked with
Time Off: 27 PTO days (incl. public holidays)
Visa sponsorship option for relocation to NYC within 2+ years
Early-stage role with high autonomy and real long-term upside
Enjoy a learning & development budget for courses, certifications, and language learning to keep growing your skills
Work where you feel most productive at co-working spaces or from your home office with support for setup, internet, and phone
We hire the best, expect the best, and give you the masterclass of your career - an archaic and huge industry like ERP only goes through a restructure like this once in a lifetime. It’s hard, it’s intense, and it’s the most rewarding work you’ll ever do.
If you’re hungry, driven, and ready to build something massive, climb aboard!
At DualEntry, we believe great products come from diverse teams. We’re an equal opportunity employer, and we’re committed to a culture where everyone feels included, supported, and able to do their best work.