Ledger - Analytics Engineer
Requirements
• Python for analysis and statistics; experience with causal inference methods is a strong plus • Familiarity with marketing/web analytics data: GA4, ad platforms (Google Ads, Amazon Ads), affiliation networks • 3-4 years of experience in data analytics/analytics engineering • Data driven and business oriented; able to challenge stakeholders' methodology • Excellent organizational skills, fluent in English • At Ledger, we are dedicated to continually investing in our employees which is why we offer more than just salaries; we provide comprehensive compensation packages that include a wide range of benefits. Here are some of the benefits you can look forward to: • Flexible work options - Our hybrid policy allows employees to work from home up to 3 times per week • Flexible work options - • Health & Wellness support - Health and Life Insurance. • Health & Wellness support - • Financial growth opportunities - Employees can become shareholders in Ledger as well as other financial benefits depending on your country of work. • Financial growth opportunities - • Commuter allowance - Ledger offers a commuter allowance to contribute to your preferred means of transportation. • Commuter allowance - • Learning & Development - A comprehensive suite of training solutions providing a personalised learning experience for every employee. • Learning & Development • For regionally specific benefits, your Talent Acquisition contact will be able to provide you with more information. • We’re committed to building an inclusive hiring process. If you need any adjustments or accommodations, just let us know, we’ll do our best to support you.
Responsibilities
• Own analytics across the full consumer sales scope: Ledger.com e-commerce, Amazon marketplaces, wholesale and resellers/distributors - covering both sell-in and sell-out- with one consistent view of revenue, units and margin reconciled in Snowflake, our source of truth • Develop and improve data models (dbt/Snowflake) across varied data sources (sales, sell-out, marketing, web analytics) with the support of the data engineering team; co-own data quality alerting (SKU, refunds, sales anomalies) • Build and maintain Tableau dashboards for business stakeholders: e-commerce performance, wholesale, resellers sell-out, affiliation, editorial content, shipping costs • Own the measurement of performance marketing channels - SEM / Google Ads, affiliation & retargeting, Amazon Ads: spend, revenue attribution, ROAS/CAC across GA4, ad platforms and internal sales data, reconciling discrepancies between sources • Measure the true impact of pricing, promotional and marketing campaigns using causal inference methods (CausalImpact, pre-post, control/synthetic groups) and recommend budget arbitrations to the Growth team • Model customer value (LTV, repurchase behavior, services attach) and feed it back into marketing ROI decisions • Contribute to cross-functional data projects (Salesforce data model, new data source integrations) and leverage AI tooling (Claude, LLM-based workflows) to scale analytics delivery • Create and deliver presentations that turn complex analyses into clear recommendations for stakeholders up to ExCom level
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