> Markdown version of [/jobs/ext/4604625-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/4604625-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Analytics Engineer

- **Company:** Wellthy, Inc.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $125,000 - $152,000
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Artificial Intelligence, Amazon Web Services, Amazon S3, BigQuery, Command-Line Interface, Data Transformation, Database Queries, Dimensional Modeling, Snowplow, Tableau (Software), Data Processing, Scripting, GitHub Copilot, Snowflake, Git, Looker Analytics, Software Version Control, Web Api
- **Published:** November 6, 2026
- **Apply:** https://www.builtincolorado.com/job/analytics-engineer/12097060?handler=ApplyRedirect

## About the Role

To be successful in this role, you'll need to be open to learning, experimenting, and evolving. Comfort with emerging technology and curiosity around how tools like AI can support your workflow or help families more effectively is a plus.

 * 2-5 years of experience in analytics engineering or a closely related role
 * Experience with analytics modeling (e.g. dimensional modeling, staging/intermediate/mart layers)
 * Strong SQL skills
 * Hands-on experience building and maintaining data transformations with dbt or similar tools
 * Comfortable using the command line and version control (git)
 * Experience querying a cloud data warehouse (e.g. Snowflake, BigQuery, or Redshift)
 * Experience using AI tools (e.g. Claude, Cursor, GitHub Copilot) to write, explain, and QA code, along with the judgment to review, test, and validate AI-generated output before it goes into production
 * Strong communicator, life-long learner, problem solver, and always curious

Qualifications that are preferred but not mandatory:

 * Experience writing basic Python scripts (e.g. for data processing, API calls, or automation)
 * Experience working with user event tracking data to support product analytics (e.g. Snowplow, Segment, Rudderstack)
 * Experience building reporting in modern BI tools (e.g. Omni, Looker, Tableau, Thoughtspot)
 * Experience automating data workflows
 * Familiarity with AWS tools (e.g. S3, Lambda), To work from home, you must have a strong internet connection, quiet space to take calls and a professional (distraction free) environment.

## Description

As an Analytics Engineer, you will help company leaders make better decisions by building and maintaining our data stack to power analysis, insights, and reports.

We love collaborating here at Wellthy and in this role you will work closely with all areas of our organization (Marketing, Product, Client Success and Care Team).

You will report directly to our VP Data, Product, and Engineering Operations.

To be successful in this role:

 * Build and maintain data transformations using dbt for analytics, and help empower end users to do self-service reporting and data exploration
 * Apply software engineering best practices to write efficient, well-tested code and contribute to improving the performance and automation of our ELT process and analytic workflows
 * Collaborate with data analysts, data engineers, and business stakeholders to gather and translate data requirements for downstream analyses and projects
 * Support company-wide efforts to improve data quality, accessibility, and governance
 * Ensure data quality and integrity by writing and maintaining tests
 * Participate in evaluations of analytics tools to help meet the needs of the organization
 * Follow and contribute to data team best practices, workflows, and documentation as we build a sustainable and scalable data function
 * Troubleshoot data issues and clearly communicate findings and processes to internal stakeholders, escalating complex problems when needed
 * Work closely with senior team members who will provide guidance on more complex modeling and architecture decisions, with opportunities to take on greater scope over time
 * Use a modern data stack of Fivetran, Snowflake, dbt, Hightouch, Snowplow, DeepNote, Metaplane, and Omni