Two Sigma Ventures

The Mission:

This is a critical and exciting time at Enigma. We’re transforming the small business financing ecosystem, and our product is gaining adoption even faster than we anticipated. This creates a new set of technical challenges for us as we continue to scale.

Over the past year we’ve made significant investments in our data infrastructure to allow engineers and data scientists to quickly deliver customer value by reliably testing and shipping changes to our data pipeline. The challenges ahead are to:

• Reduce overall runtime of our data pipeline
• Improve computational efficiency to reduce costs

The Role:

This is a role responsible for developing and implementing our strategy for driving data processing efficiency. Your impact will be measured by:

• The increase in the team’s capability to optimize data transformations (combination of methodology and tooling)
• The specific improvements we achieve in processing time and computational cost

This role has an important hands-on component - you’ll be showing the team what good looks like. However, your greatest impact will be in the technical strategy you’ll formulate and the close coaching and mentorship you’ll provide to team members.

We’re looking for someone who:

• Is motivated by leading engineers to increase the efficiency and speed of complicated data processing systems
• Thrives as a coach and mentor and measures their impact by the increase in capabilities of the team
• Operates with a bias for action and knows how to deliver value in the short, medium and long term
• Adopts a principled approach to difficult data processing problems and demonstrates expertise and excellence in their engineering craft
• Operates transparently, collaboratively and with low ego—loves learning from others and having their ideas questioned and challenged

What makes this job interesting?

• Impact: Your decisions will determine the speed at which we can scale to take on new customers and impact the developer experience of dozens of teammates.
• Technical Challenge: You will take on some of our thorniest technical problems and render them tractable.
• Leadership: Success in this role will achieved through building the team’s capabilities and influencing our engineering culture.

Our ideal candidate:

• Knows Databricks and Spark inside and out
• Brings a clear point of view on data processing optimization, data modeling, cluster management and Databricks performance techniques
• Has a strong track record of technical leadership to grow and scale teams

About Us:

At Enigma, we’re building the single, most reliable source of data on businesses to power the future of financial services. By engineering better data from hundreds of public and third-party sources, we aim to tell the complete story of every business, so that companies of every size can access the financial services they need to grow and thrive. Our core values – generosity, curiosity, ingenuity, & drive – guide everything we do, from how we make our most important product decisions to how we work with and support one another on a daily basis. We’re a team of curious, driven individuals with diverse backgrounds and skills, but we’re all passionate about engineering deeper understanding through data—together. If this resonates, we would love to hear from you!

We are proud to be an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Salary Range: $180,000-$240,000

A note on salary ranges: we pride ourselves on paying competitively for our size and industry. Salary is one piece of a total Enigma compensation package that includes additional benefits and opportunities. All of our compensation packages include equity because we believe 100% of Enigma employees should have the option to purchase ownership in the company and benefit from the value we’re creating together.