Lead Analytics Engineer

7+ years of relevant analytics or data science experience
2+ years of experience SaaS and/or enterprise software business models
3+ years developing revenue reporting and forecasting models
Fluency in SQL with proficiency in SQL development
Hands-on experience with Python or R
Ability to translate business requirements into technical specifications
Proficient in using data modeling and visualization platforms; Looker is a plus
Skilled in leveraging tools like dbt for cleaning, transforming, testing, and deploying analytics-ready datasets
Experienced in managing and working with Data Lakes or Data Warehouses such as Snowflake, Trino, Redshift, and BigQuery
Strong communication skills, with the ability to collaborate effectively and translate complex datasets or queries into clear, accessible insights for non-technical audiences
Familiar with working with APIs for data integration and analysis
Ability to learn general functional and technical aspects of firm’s Financial and GTM systems whenever required
Strong knowledge of Salesforce data structures

Design and maintain Maven’s data transformation and analytics infrastructure to support Revenue Operations, Finance and Go-to-Market (GTM) teams
Build tools to automate enrollment forecasts, integrating key inputs from Customer Success, Member Growth Marketing (MGM), and Strategic Finance teams
Partner with the GTM Architect, Salesforce Admin, and account leaders to design and develop data structures for financial and GTM reporting. Cleanse and integrate historical datasets while implementing data governance to ensure accuracy and consistency (primarily using SQL and Python)
Develop an understanding of Salesforce to effectively structure and utilize data, enabling comprehensive reporting on the deal lifecycle—from lead generation to revenue recognition
Drive operational efficiency by identifying areas for process improvement and recommending highly scalable solutions
Act as a bridge between Revenue Operations, Product, Finance, Business Intelligence, and Engineering teams to optimize data structures and maximize actionable insights.