Lead Analytics & Data Engineer

DualEntry is one of the world’s fastest-growing AI startups focused on transforming the finance industry with their AI-native ERP solutions. The Lead Analytics & Data Engineer will establish a Data & Analytics function from the ground up, driving data infrastructure and insights across various teams to enable better decision-making.

Responsibilities:

• Drive both data infrastructure and data insights across product, engineering, GTM and marketing from the ground up
• Full stack analytics engineering development, building models to consume, transform, and expose data internally and externally
• Work 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

Requirements:

• 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