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Design and build scalable data pipelines and dimensional data marts, and maintain AI‑native tooling like Hermes and Ralph. Provide self‑service analytics support, enforce data quality, governance, and security, and help define analytics engineering standards.
4+ years of analytics or data engineering experience with a modern stack (Fivetran, Airflow, Snowflake, dbt, etc.), strong SQL and Python skills, and familiarity with dimensional modeling. Ability to use AI agents to boost productivity and collaborate across data, product, and engineering teams.
The role powers Mercury’s AI‑native data platform, delivering reliable analytics that accelerate product development and enable AI‑driven customer experiences. Robust data products are essential for meeting the company’s bank charter and scaling its fintech operations.
Candidates who are curious, action‑oriented, and empathetic collaborators who enjoy building reusable, scalable data platforms. Ideal for those who thrive on cross‑functional impact and may have fintech or agentic workflow experience.
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.
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:
