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Senior Analytics Engineer

Remote

Lithic creates card issuing and payment infrastructure for technology companies that just works. We help some of the world’s fastest-growing digital banks, fintech companies, and software companies process billions in transactions annually.

The Analytics team at Lithic empowers the organization with data-driven insights and scalable solutions. We sit within the engineering division and manage a self-serve business intelligence ecosystem, provide dedicated support to key teams, and build data products that drive internal and external decision-making. Our data model, built in DBT and Snowflake, enables accurate reporting, dashboards, and deep analysis. We value curiosity, challenge each other to think critically, and strive to make data accessible and impactful across the company.

As a Senior Analytics Engineer at Lithic, you'll be a key contributor to our data platform and the data products that power our business. You'll work cross-functionally with teams across Product, Risk, Operations, and Finance to build and scale robust data solutions that drive strategic decision-making and operational excellence.

What You'll Do

  • Work with real-time payments data at massive scale and help shape the future of our data platform as we grow
  • Design and implement data models that enable critical business functions across the organization
  • Build and maintain data products that support automated reporting, customer-facing analytics, and operational workflows
  • Collaborate with the Risk team to develop monitoring systems and analytical frameworks for risk assessment
  • Support the Operations team with data infrastructure that streamlines business processes and improves efficiency
  • Establish and promote best practices for data governance, quality, and documentation
  • Mentor other team members and contribute to the evolution of our analytics engineering practices

What You'll Bring

  • Proven experience in analytics engineering or data engineering roles, with a track record of building impactful data solutions
  • Strong SQL skills with experience in modern data warehouse environments (Snowflake preferred)
  • Expertise with DBT or similar data transformation frameworks
  • Proficiency in Python and version control workflows (Git)
  • Curiosity about, and ideally experience with using AI tools to develop high quality work products
  • Experience working with cross-functional stakeholders to translate business needs into technical solutions
  • Ability to work with various types of data including transactional, financial, and operational datasets
  • Comfort with ambiguity and ability to drive projects forward with minimal oversight

Our Ideal Candidate

You're a versatile analytics engineer who enjoys tackling diverse challenges across different business domains. You thrive on ownership and approach problems at a goal level rather than a task level. You're excited about building systems that scale and enable others to self-serve their data needs. You understand that great data infrastructure requires both technical excellence and a deep understanding of the business context. You have good hunches about when to prefer simplicity over complexity. You enjoy collaborating with stakeholders to uncover true needs and delivering solutions that exceed expectations.

Base Salary: $141,000 - $191,000

 

Benefits: 

  • Health, vision, and dental insurance; HSA Contribution Match
  • Unlimited PTO
  • 401(k) match 
  • Voluntary Life Insurance and AD&D 
  • 3% cashback on all Privacy purchases
  • 12-weeks fully paid parental leave
  • Work From Anywhere: work from anywhere in the world 4-weeks each year
  • 5-Year Fully Paid 4-Week Sabbatical Program

We believe in-person collaboration boosts creativity, communication, and agility, which are key to our growth. Employees in the NYC area are asked to work from our SoHo office three days a week - Tuesdays and Thursdays are core in-office days - the third is flexible.

In-office employees receive: 

  • $50/month towards your commute
  • Free lunch every Tuesday and Thursday

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