Senior Analytics Engineer

Paid holidays and flexible, take-it-as-you-need-it scheduled time off

A culture built on innovation that values big ideas, no matter where they come from

A MacBook set up and ready from day one, plus a $500 stipend to design your ideal workspace

Equity in a rapidly growing startup backed by top-tier VCs

TO BE CONSIDERED FOR THIS ROLE, PLEASE SUBMIT AN UPDATED RESUME TRANSLATED TO ENGLISH

Role Overview

As a Senior Analytics Engineer I, you operate as an experienced individual contributor on the Analytics Enablement Team, which owns the core data infrastructure, data modeling architecture, and governance standards that support decision-making across HCP. You independently translate ambiguous business questions into scalable, well-documented data models and help ensure that information remains consistent and trustworthy from the underlying data model through the semantic layer and downstream analytics tools.

You apply strong technical judgment when evaluating modeling patterns, architecture, performance, and data quality. You own significant areas of the data model, contribute to shared metric definitions, and strengthen the standards that allow teams to confidently build on our analytics ecosystem. You also provide technical guidance, thoughtful code reviews, and documentation that help other analytics engineers improve their work and successfully navigate our tools and standards.

Our team is passionate, empathetic, hard working, and above all else focused on improving the lives of our service professionals (our Pros). Our success is their success.

What you do each day:

Design, develop, and maintain scalable data models and marts in dbt and Snowflake that support business intelligence and analytics across multiple functions

Evaluate and communicate architectural tradeoffs related to modeling patterns, data layering, maintainability, performance, and scalability

Define and maintain consistent metrics across source data, transformed models, the Omni semantic layer, and downstream reporting tools

Govern semantic layer standards by reviewing model and topic changes for consistency, documentation, quality, and long-term maintainability

Strengthen governance processes that keep shared data models and the semantic layer trustworthy as adoption grows across HCP

Build AI-enabled tools, workflows, context, and guardrails that expand responsible self-service analytics and reduce manual analytics work

Partner with Finance, Marketing, Product, Sales, and other stakeholders to translate ambiguous business needs into effective technical solutions

Own data quality within assigned areas by monitoring performance, investigating discrepancies, and resolving issues before they affect downstream users

Document models, workflows, metric definitions, and architectural decisions so others can confidently build on and maintain the work

Provide technical guidance, code reviews, and onboarding support to analytics engineers while reinforcing team standards and best practices

Qualifications:

5+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a closely related technical field

Bachelor’s degree in Computer Science, Statistics, Information Systems, Data Science, or a related field, or equivalent work experience

Advanced proficiency in SQL and hands-on experience developing, testing, and maintaining production data models in dbt and Snowflake

Experience working with semantic layer or business intelligence tools (i.e. Omni, Looker, Tableau) and orchestration tools (i.e. Airflow, Dagster)

Working proficiency in Python and experience applying software development practices such as version control, testing, code review, and documentation

Demonstrated ability to leverage AI tools to improve workflows, streamline execution, or enhance outputs

What will help you succeed:

Strong technical judgment with the ability to transform loosely defined business problems into scalable, maintainable, and well-documented data solutions

Clear communication skills with the ability to explain technical tradeoffs and business impact to both technical and non-technical stakeholders

High attention to detail and a consistent commitment to data accuracy, reliability, and quality

A collaborative approach to technical mentorship, feedback, documentation, and cross-functional problem-solving

A proactive ownership mindset with the ability to identify risks, resolve issues, and move complex work forward with limited direction

Exceptional breadth of interest shown through tangible, self-initiated ventures or deep community involvement; you love trying new things and may possess a demonstrated history of successfully pivoting or starting over in life and work

Compensation starts at $5,500 USD per month.