Senior Analytics Engineer

Mercury • Portland, OR

2d

About The Position

In 1989, Tim Berners-Lee envisioned a system to help CERN scientists share information more effectively. That vision became the World Wide Web – transforming how humanity connects and shares knowledge. Today, we're looking for someone who can architect the next evolution in how Mercury processes, understands, and acts on data.
We’re hiring a Senior Analytics Engineer to help build the data foundation that accelerates Mercury’s transition to an AI-native analytics platform. 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 things like propensity models and agentic workflows. Come grow with us.

Requirements

• 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
• 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 stakeholders where they’re at and helping them succeed
• Discern what’s needed from what’s wanted to deliver maximum impact

Nice To Haves

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

Responsibilities

• Design and build scalable data pipelines and business-conformed dimensional data marts in collaboration with Data Science, Engineering, Product, and Operations departments
• Support adoption of agentic tooling, 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 best practice

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed