Data Engineer

Candid Health•Denver, CO

16d•$165,000 - $205,000

About The Position

We’re looking for a passionate and skilled Data Engineer to join our fast growing data team to revolutionize healthcare billing products and systems that directly address the needs of our customers. As an early Data Engineer, you’ll play a key role in designing, building, and supporting the next generation of our data infrastructure. This is an opportunity to get in at the ground floor of designing and building something exciting, new, secure, durable, performant, and maintainable.

Requirements

Bachelors of Science or Bachelors of Art in Computer Science, Computer Engineering, Math or other similar degree.
4+ years of experience working with data pipelines, products, and tools.
You’ve built and maintained complex data integrations or pipelines.
You have well-developed opinions on modern data warehouse architecture, tools, and patterns.
You have excellent technical vision; you know the right architecture and patterns to build functional, durable, and maintainable product.
You have a customer-first and learner’s mindset, and value teaching others.
You make the right trade-offs when considering project scope, which corners are worth cutting, and which are not.
You’re a clear and concise communicator; you enjoy the challenge of explaining complicated ideas in simple terms, both in-person and in writing.

Nice To Haves

Experience with Google Cloud Platform, BigQuery, PostgreSQL, Metabase, Terraform, Python.

Responsibilities

Collaborate with leadership and other stakeholders including engineering, delivery, product, and customers to understand Candid’s data needs.
Work with product and engineering to understand the long-term product strategy and broader technical architecture.
Work with customers to understand their needs and how best to address them in a scalable way.
Expansively own Data Engineering team outcomes: Deliver on Data Team outcomes for both internal teams and external customers, which include both operational and analytics workflows.
Own the design of new data infrastructure: Research and identify industry best practices and state-of-the-art tools to leverage. Design new systems to support the necessary outcomes in a secure, durable, performant, and maintainable way.
Build and support new data products: Build datasets, pipelines, and other solutions to support operational and product outcomes. Develop support systems to scale the team and achievable outcomes.
Contribute significantly to building a robust data culture: ensuring data is trusted, accessible, and central to how we identify opportunities and measure our impact.