Senior Analytics Engineer

About Eucalyptus

Eucalyptus is dedicated to improving long-term health outcomes for a large global population. The company is part of Hims & Hers, a personalised health and wellness leader. Eucalyptus operates the Juniper program, a major weight-management initiative that combines GLP-1 medication with structured nutrition, movement, and clinician support from prescribers, nurses, coaches, pharmacists, and dietitians. Clinical research indicates this combined approach helps patients lose four times more weight than standard methods. The organisation serves patients across multiple countries and has received selective NICE endorsement for NHS services.

About the Role

Eucalyptus is seeking a Senior Analytics Engineer to ensure the accuracy, reliability, and scalability of financial data and reporting across all brands. The role operates at the intersection of finance, commercial, data, operations, and engineering. You will own the standardisation of financial models worldwide, ensuring consistency and documentation for both internal management and external regulatory reporting. The position requires close collaboration with finance and commercial teams to define requirements, and with engineering and operations teams to shape data collection. Full end-to-end ownership is expected, including implementation, governance, data quality monitoring, and documentation as the company scales.

Key Responsibilities

Revenue Models

You will maintain and enhance the accuracy and reliability of core orders, revenue, and refunds models. This includes configuring and managing integrations with financial reporting platforms such as NetSuite. You will standardise reporting for each operating region, including the UK, European Union, Australia, Japan, and Canada. Collaboration with engineering and operations will be necessary to manage product and process changes, reducing downstream reporting impacts.

SEC Reporting Models

You will work directly with the US Hims & Hers finance team to provide accurate, reliable, and well-documented data for SEC reporting. This involves building automated checks for data reliability and monitoring drifts in reported figures. You will maintain a deep understanding of upstream source data to assess change impacts on financial figures.

Payback Models

You will accurately model product cost of goods sold and service costs, integrating these with revenue data to build payback models. These models will inform capital allocation decisions. Close partnership with finance, commercial, and operations teams will be required to maintain product COGS data. You will also work with marketing teams to accurately track and attribute spend across channels such as Google, Facebook, and TikTok.

Data Quality and Validation

You will monitor and validate data accuracy across all financial source data. This includes building automated checks for missing or duplicated data, schema drift, and anomalies. Investigating discrepancies between source data and reported figures will be a regular task. You will also maintain comprehensive end-to-end documentation for all reporting models.

About You

You bring six or more years of experience in analytics engineering, finance, or commercial analytics. You have a proven track record of building and maintaining production data models that serve multiple stakeholders. Your SQL skills are strong, particularly in BigQuery, for data modelling and validation. You are detail-oriented and capable of self-verifying assumptions and identifying data gaps. You take ownership of outcomes and decisions, with a strong commitment to documentation. Experience with dbt or similar transformation tools is essential.

Key Facts

What You'll Do

You will design intake workflows to capture finance requirements clearly before models are constructed. You will build revenue and order models in BigQuery, ensuring logic correctly handles refunds and multi-brand rules. You will review data outputs against source systems to confirm accuracy for SEC and external reporting. You will deliver standardized dashboards in NetSuite that align finance, commercial, and operations teams globally. You will partner with engineering to manage product and process changes, minimising downstream reporting risk. Guarding data quality will be a priority, achieved through automated checks for duplicates, schema drift, and anomalies. You will validate COGS and service cost models so payback calculations reflect true product economics. You will monitor marketing spend attribution across digital channels for accuracy.

Requirements

You will possess 6 or more years of experience in analytics engineering, finance, or commercial analytics contexts. You will demonstrate experience building and maintaining production data models for multiple stakeholders. You will write strong SQL, especially in BigQuery, for modelling and thorough validation. You will show a detail-oriented mindset that enables self-verification of assumptions and data gaps. You will own outcomes with a strong sense of responsibility for decisions and documentation. You will use dbt or similar transformation tools to manage changes in data pipelines.

Nice to Have

Experience working with Juniper or similar high-volume commercial platforms is a advantage.

Skills & Tools

Proficiency in BigQuery, NetSuite, dbt, and SQL is required.