Senior Analytics Engineer

Job not on LinkedIn

🔥 3 minutes ago

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

🏄 California, New York, +1 more states – Remote

🏄 California – Remote 🗽 New York – Remote 🌲 Oregon – Remote

💵 $166.6k - $208.3k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

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Mercury

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

💳 Fintech

🏦 Banking

☁️ SaaS

Fintech • Banking • SaaS

Mercury is a software-driven fintech that provides business and personal banking products built for startups and small to mid-size companies. Its platform offers business checking and savings, Treasury products, business credit cards and spend management, payments and invoicing, accounting integrations and AI-powered automations, plus APIs and developer tools. Mercury partners with FDIC-insured banks to offer deposit protection, emphasizes virtual cards, granular spend controls, and workflow automations for teams, agencies, ecommerce brands, VC funds, and crypto businesses. The product is positioned as an all-in-one banking and finance platform delivered through a modern app and API.

📋 Description

• Design and build scalable data pipelines and business-conformed dimensional data marts with Data Science, Engineering, Product, and Operations • Support development and adoption of agentic tooling, including Mercury’s AI Data Analyst (Hermes) and dbt Agent (Ralph) • Support self-service analytics workflows, Analytics Engineering skills, and dimensional data principles through implementation, education, and peer support • Implement data and analytics products needed to effect Mercury’s bank charter • Contribute to data quality, governance, and security strategies • Contribute to Analytics Engineering standards and best practices • Build shared data foundations powering decisioning, automation, and measurement across Mercury • Enable durable data products, faster experimentation, propensity models, agentic workflows, and data-driven customer experiences

🎯 Requirements

• 4+ years of Analytics or Data Engineering experience • Expertise working in a full modern data stack including Fivetran, Airflow, Snowflake, dbt, Omni, Hex, or equivalents • Proficiency with SQL • Working experience with Python • Proficiency using AI agents to accelerate work • Experience with dimensional data modeling principles and building data for scale • Ability to prioritize reusable, scalable deliverables • Ability to deliver readable code, strong tests, and quality documentation • Banking or financial services industry experience may be an additional qualification • Experience with agentic development and/or analytics workflows may be an additional qualification • Exposure to data governance, compliance, and security best practices may be an additional qualification • Full-stack mindset and willingness to solve problems end-to-end may be an additional qualification

🏖️ Benefits

• Base salary • Equity (stock options/RSUs) • Benefits • Reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs