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Senior Analytics Engineer

Mercury

LocationUnited States, Canada
SenioritySenior
CompanyMercury
Verified recentlyChecked today
Compensation

$157k-$208k

Salary details are shown when available from the source listing. Sign in before applying so the role can be reviewed against your resume, salary goals, seniority, timezone, and location eligibility.

Requirements and working style

Decision details from the source listing

Experience

4+ years stated

Education

High school

Schedule

unspecified

Benefits stated
Equity (stock options/RSUs)Benefits

These fields are normalized from the employer's text. Confirm details on the employer site before applying.

WFH.team analysis

What this posting tells you

Senior Analytics Engineer at Mercury, building data pipelines, dimensional data marts, self-service analytics, and AI-agent-supported data workflows. Remote within the United States or Canada. The stated US base salary range is $166,600–$208,300 USD; the listing separately gives a Canadian range in CAD.

Role lane

Backend, Customer success, Data, Education, Finance and investments, HR and recruiting, Operations, Product, Security, Software

Where you can work

United States, Canada

Working hours

Timezone overlap is not stated.

Arrangement

Senior · full_time

Required signals
Analytics engineeringData engineeringSQLPythonModern data stack (Fivetran, Airflow, Snowflake, dbt, Omni, Hex, or equivalents)Dimensional data modelingAI agentsData qualityReusable, scalable data products
Preferred signals
Banking or financial services experienceAgentic development or analytics workflowsData governanceComplianceData securityFull-stack mindset
Confirm before applying
  • Required timezone overlap is not stated
Market context

Backend hiring on WFH.team

3,730active related roles
1,081new in the latest period
162.8jobs per 100 candidates
$186kmedian of comparable listed ranges

This role's listed pay is near the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.

Explore the remote job market
Skills and signals
Analytics engineeringData engineeringSQLPythonModern data stack (Fivetran, Airflow, Snowflake, dbt, Omni, Hex, or equivalents)Dimensional data modelingAI agentsData qualityReusable, scalable data productsBanking or financial services experienceAgentic development or analytics workflowsData governanceComplianceData securityFull-stack mindsetRemote within the United States or Canada; also lists San Francisco, New York, and Portland as locations.
Job description

Senior Analytics Engineer at Mercury

In 1989, Tim Berners-Lee wrote a proposal for CERN. CERN lost knowledge when people left, because its information was in many systems that did not connect. His solution was simple: link documents so that all people can find them and use them. That proposal became the World Wide Web.

Mercury has a similar challenge with data. Teams, models, and AI agents need data that they can find, understand, and trust. We are building an AI-native data platform that enables Mercury to have reliable analytics, accelerate product development, and enable the next generation of AI-powered products and internal tools.

We are hiring a Senior Analytics Engineer to help us accelerate. You’ll join a team of high-performing Data and Analytics Engineers building the shared foundations that power decisioning, automation, and measurement across the company, collaborating closely with Data Scientists and partners in Product, Engineering, and Operations. Your curiosity and bias toward action will drive meaningful impact as you build durable data products, unlock faster experimentation, and help teams ship propensity models, agentic workflows, and amazing data-driven experiences for our customers. Come grow with us.

Responsibilities

  • Design and build scalable data pipelines and business-conformed dimensional data marts in collaboration with Data Science, Engineering, Product, and Operations departments
  • Support the development and adoption of agentic tooling. We have our own AI Data Analyst (Hermes) and dbt Agent (Ralph) that are built and managed by our Analytics Engineers
  • Support self-service analytics workflows, Analytics Engineering skills, and dimensional data principles through implementation, education, and peer support
  • Help us implement the data and analytics products we’ll need to effect our bank charter
  • Contribute to the evolution of our data quality, governance, and security strategies
  • Contribute to our definition of Analytics Engineering standards and best practices

You may be a good fit if you

  • Have 4+ years of Analytics or Data Engineering experience
  • Have expertise working in a full modern data stack including Fivetran / Airflow / Snowflake / dbt / Omni / Hex or equivalents
  • Are proficient with SQL and have working experience with Python
  • Proficient using AI agents to accelerate your and your teammates’ work
  • Have experience with dimensional data modeling principles and building data for scale
  • Treat data products as a platform by prioritizing reusable, scalable deliverables
  • Deliver readable code, strong tests, and quality documentation
  • Experiment responsibly and share what you learn so everyone benefits
  • Practice relentless empathy by meeting your stakeholders in Data, Product, Engineering, and beyond where they’re at and helping them succeed
  • Discern what’s needed from what’s wanted to deliver maximum impact

Strong candidates may additionally have

  • Banking* or financial services industry experience
  • Experience with agentic development and/or analytics workflows
  • Exposure to data governance, compliance, and security best practice
  • A full-stack mindset and willingness to solve problems end-to-end by flexing into Data Engineering and Data Analysis

If this role interests you, we invite you to explore our public demo at demo.mercury.com .

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

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Total Rewards

The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following :

US employees (any location)

$166,600 — $208,300 USD

Canadian employees (any location)

$157,400 — $196,800 CAD

Company context

Working remotely at Mercury

We’re building banking for startups. We emphasize beauty and usability, and customers seem to love our product.

Team size
201-500
Founded
2016
Application process

Review current openings on Mercury's official careers page before applying.

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