About Ethos

Ethos was built to make it faster and easier to get life insurance for the next million families. Our approach blends industry expertise, technology, and the human touch to find you the right policy to protect your loved ones. 

We leverage deep technology and data science to streamline the life insurance process, making it more accessible and convenient. Using predictive analytics, we are able to transform a traditionally multi-week process into a modern digital experience for our users that can take just minutes! We’ve issued billions in coverage each month and eliminated the traditional barriers, ushering the industry into the modern age. Our full-stack technology platform is the backbone of family financial health.

We make getting life insurance easier, faster and better for everyone. 

Our investors include General Catalyst, Sequoia Capital, Accel Partners, Google Ventures, SoftBank, and the investment vehicles of Jay-Z, Kevin Durant, Robert Downey Jr and others. This year, we were named on CB Insights' Global Insurtech 50 list and BuiltIn's Top 100 Midsize Companies in San Francisco. We are scaling quickly and looking for passionate people to protect the next million families! 

About the Role

Ethos is an extremely data driven company. We take every decision backed by data. Making data and insights available to everyone in the company is the mission of data engineering team. You will work with some of the brightest people helping drive infrastructure and insights to disrupt one of the oldest and largest industries in the country.

Our stack: Our backend is built in Node.js and Postgres and is totally hosted on AWS. Our front end is built in React/Redux.

Duties and Responsibilities:

  • Develop and maintain robust ETL pipelines to support data needs across the organization.
  • Contribute to the development and governance of the data warehouse.
  • Build and maintain data marts to support various business functions.
  • Optimize queries, and refine data structures to ensure efficient data retrieval and reporting.
  • Build and maintain systems to ensure data accuracy, consistency, and availability across systems.
  • Set up and maintain automated CI/CD pipelines for model training and deployment.
  • Develop and maintain a centralized feature store to ensure consistency between training and serving features.
  • Develop end-to-end automation of ML model deployment, ensuring smooth transition from development to production.
  • Implement tools and processes to monitor the performance of ML models in production, ensuring that they are performing as expected and maintaining their accuracy.
  • Ensure that all data warehouse activities adhere to regulatory standards, data privacy rules, and company policies.
  • Conduct regular reviews of data infrastructure to identify areas of inefficiency, underutilization, or redundancy.
  • Research and implement best practices for cost optimization across the data stack.
  • Work closely with other teams, including but not limited to data scientists, business analysts, and product managers, to understand and meet their data requirements.

Qualifications and Skills:

  • 4+ years of experience in Software engineering.
  • Proficiency in a programming language, preferably Python.
  • Proficiency in SQL & data modeling.
  • Strong understanding of SWE methodologies, CI/CD and testing.
  • Strong understanding of ETL processes, data warehousing, and data governance principles.
  • Experience building and managing data intensive applications.
  • Experience with large scale MPP databases.
  • Preferred experience with MLOps, including ML model deployment, monitoring, and lifecycle management. Familiarity with tools and platforms like MLflow, Kubeflow, or sagemaker.
  • Preferred experience with Snowflake, Airflow & DBT.
  • Preferred experience with stream processing frameworks such as Flink.

#LI-Hybrid

#LI-JS4

Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. At Ethos we are dedicated to building a diverse, inclusive and authentic workplace.

We are an equal opportunity employer who values diversity and inclusion and look for applicants who understand, embrace and thrive in a multicultural world. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Pursuant to the SF Fair Chance Ordinance, we will consider employment for qualified applicants with arrests and conviction records.

To learn more about what information we collect and how it may be used, please refer to our California Candidate Privacy Notice.

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