- 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.
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