Data Infrastructure Engineer

Overview

Notable is the leading intelligent automation company for healthcare. Customers use Notable to drive patient acquisition, retention, and reimbursement, scaling growth without hiring more staff. We don’t just make software. We are on a mission to fix the broken U.S. healthcare system by helping to eliminate the massive administrative burden that is placed on our nation’s healthcare staff. We hire people from diverse backgrounds and are always looking for employees who bring fresh ideas to our space. Passion is paramount, and at Notable, you will get to work with other talented people who aim to set the new standard for innovation in healthcare.

As a Data Infrastructure Engineer at Notable, you will have the opportunity to help us continue to rapidly scale our platform and infrastructure, interfacing directly with our engineering teams. You will be responsible for designing and implementing the core infrastructure underlying the entire Notable platform and have a huge influence on the continuous improvement of our infrastructure reliability and security, all while addressing the challenges of scale and engineering velocity. In addition, you will work hand-in-hand with our Intelligence team to build and maintain data pipelines that fuel both our business decisions and ML/AI capabilities.

Key Responsibilities:

• Design and implement scalable, secure infrastructure to support our growing platform.

• Collaborate with engineering teams to enhance infrastructure reliability and performance.

• Debug and resolve issues across services and infrastructure.

• Build and maintain data pipelines in support of ML/AI initiatives.

• Contribute to the continuous improvement of our infrastructure and processes.

• Automate build, test, package, release, and configuration management.

Requirements:

• 5+ years of relevant work experience.

• Excellent problem-solving, debugging, and programming skills.

• Experience in automating and implementing CI/CD workflows.

• Strong technical communication and collaboration skills.

• Understanding of the Software Development Life Cycle (SDLC).

• Experience with distributed data warehouse systems such as Databricks, RedShift, BigQuery, Spark
  experience with machine learning (MLOps) and data infrastructure

• Familiarity with cloud computing platforms like GCP or AWS.

• History of leveraging open-source and commercial solutions to deliver value.

• Demonstrable ability to strike the right balance between speed and quality.

Bonus Points:

• Experience with MLOps practices and tools.

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