Senior Analytics Engineer
Mercury · Data · Senior · 1mo ago
$167k – $208k
per year
Open to candidates living in Canada, United States.
Direct from the employer's own careers page
Who can apply
Read straight from the listing, so you know before you spend time on it.
Open to candidates living in Canada, United States.
“San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States”
Team members are based in San Francisco, New York, Portland, or working remotely across the United States and Canada.
- Async-first
- The listing doesn't promise async-first working.
- Contractor / B2B
- No mention of hiring international contractors or invoicing.
- Global stipend
- No home office or equipment budget mentioned.
- Annual retreat
- No company-paid get-togethers mentioned.
Read from the listing automatically. Always confirm the details with the company before you accept an offer.
About the role
As a Senior Analytics Engineer at Mercury, you will join a high-performing Data and Analytics Engineering team building shared data foundations across the company. You will partner with Data Scientists, Product, Engineering, and Operations to design durable data products, accelerate experimentation, implement products needed for Mercury's bank charter, and evolve custom AI agentic tooling such as Hermes and Ralph.
What you'll do
- Design and build scalable data pipelines and business-conformed dimensional data marts in collaboration with Data Science, Engineering, Product, and Operations
- Support the development and adoption of internal AI agentic tooling, including an AI Data Analyst (Hermes) and dbt Agent (Ralph)
- Support self-service analytics workflows, analytics engineering skills, and dimensional data principles through education and peer support
- Help implement data and analytics products needed to effect Mercury's bank charter
- Contribute to data quality, governance, security strategies, and Analytics Engineering best practices
What you bring
- 4+ years of Analytics or Data Engineering experience
- Expertise working in a modern data stack such as Fivetran, Airflow, Snowflake, dbt, Omni, Hex, or equivalents
- Proficiency with SQL and working experience with Python
- Experience with dimensional data modeling principles and building scalable data products
- Proficiency using AI agents to accelerate workflows and tasks
About Mercury
Mercury is a fintech company building banking and financial software products designed to power the next generation of ambitious companies.
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