Data Engineer: Analytics

Slash is building the future of business banking, one industry at a time. We believe businesses deserve financial infrastructure tailored to how they actually operate. That's why we're creating a new category of business banking. We combine the reliability of traditional banking (high yields, competitive rewards, and comprehensive security) with industry-specific features that make businesses more efficient, more competitive, and more profitable.

Started in 2021, Slash is one of the fastest growing fintechs in the world and we power over three billion dollars a year in business purchasing across numerous industries. We're backed by some of the best investors in the world including Menlo Ventures, NEA, Y Combinator, Stanford University, and the founders of Tinder and Plaid. Slash is headquartered in San Francisco, and has a strong in-person culture.

Slash is, at its core, a technology company and is on a mission to build the best engineering team in the world. We’re looking for a Product Data Analyst to own end-to-end data workflows that support critical decisions across product, operations, risk, and growth. You’ll help define what we track, ensure we trust what we see, and uncover insights that shape how we build.

You’ll work closely with product and engineering to instrument new features, analyze customer behavior, and guide key decisions with data. You’ll also help shape the internal analytics stack that keeps our team fast and informed.

If you enjoy solving messy data problems, love digging into product metrics, and want a front-row seat at a high-growth fintech startup, this role is for you.

• Build dashboards, deep-dive reports, and flexible queries to support key business functions

• Partner with product, ops, and engineering to define metrics and ensure accurate event tracking

• Translate vague product questions into sharp analytical insights and recommendations

• Maintain and improve our internal analytics stack (dbt, Postgres, Metabase)

• Writes expert-level SQL and can translate complex business questions into performant queries

• Is comfortable working in tools like dbt, Metabase, or similar

• Understands how to define, track, and maintain clean product metrics

• Has experience working with large or messy datasets and making them usable

• Work directly with the CEO every day to solve the highest priority company tasks

• Opportunity for high growth

• High autonomy + ownership culture

• High ownership over analytics in a high-velocity startup

• Competitive pay + equity package

• Unlimited PTO, Health, Vision, and Dental coverage