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greenhouse

Senior Analytics Engineer

Mercury
Remote, USA
Full-time
Senior · 4+ years experience
Remote
USD 166600-208300 yearly / year
Discovered 2 weeks ago
dbt

Full Job Posting

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

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