Data Engineer

Ethos is seeking a highly skilled and experienced Data Engineer to join their team. As a data-driven company, Ethos values the importance of making data and insights available to everyone in the organization. The Data Engineer will be responsible for developing and maintaining robust ETL pipelines, contributing to the development and governance of the data warehouse, and optimizing queries and data structures. They will also be involved in setting up automated CI/CD pipelines, developing end-to-end automation of ML model deployment, and ensuring data accuracy and consistency. The ideal candidate will have at least 4 years of experience in data engineering.

• 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.

• 4+ years of experience
• Strong experience in developing and maintaining ETL pipelines
• Proficiency in building and maintaining data warehouses and data marts
• Expertise in optimizing queries and refining data structures for efficient data retrieval and reporting
• Knowledge of setting up and maintaining automated CI/CD pipelines for model training and deployment
• Experience in developing and maintaining a centralized feature store
• Familiarity with end-to-end automation of ML model deployment
• Ability to implement tools and processes for monitoring the performance of ML models in production
• Understanding of regulatory standards, data privacy rules, and company policies related to data warehouse activities
• Ability to conduct regular reviews of data infrastructure to identify areas of inefficiency, underutilization, or redundancy
• Knowledge of best practices for cost optimization across the data stack
• Strong collaboration skills and ability to work closely with other teams to understand and meet their data requirements.

• Fast and convenient life insurance process
• Accessible and modern digital experience
• Full-stack technology platform
• Opportunity to work with bright and passionate people
• Data-driven decision-making
• Opportunity to disrupt a large industry
• Opportunity to work with industry-leading investors
• Opportunity for career growth and scaling quickly
• Opportunity to protect millions of families
• Opportunity to work with a diverse and inclusive team
• Equal opportunity employer
• Emphasis on diversity and inclusion
• Consideration for applicants with diverse backgrounds
• Privacy and data protection measures in place