Ethos Life
life insurance technology
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at Ethos Life. Skills: Data Platform development, Distributed workflow systems, Python libraries, Data infrastructure administration, Cost governance, Snowflake administration, Production code ownership, Automation for service and ML model deployment, Performance, reliability, and health monitoring, Platform capabilities for data marts. Build and operate internal data platforms, services, and distributed workflow systems (Temporal, Airflow). Write and maintain internal Pytho”
Industry & Context.
What They're Looking For.
Must Have
5+ years of experience in software engineering, Proficiency in at least one programming language such as Go or Python, Experience building and maintaining backend systems, internal tools, or platform applications in production environments, Understanding of software engineering fundamentals, including data structures, algorithms, concurrency, and system design, Understanding of software development best practices, including CI/CD, automated testing, code review, and observability, Proficiency in SQL and data modeling, Understanding of ETL processes, data warehousing, and data governance principles, Experience building and managing data-intensive or distributed applications, Experience designing and operating APIs, services, and workflow-based systems
Nice to Have
Experience with Go & Python in production environments, Experience with workflow orchestration platforms such as Temporal, Experience building internal developer platforms or business-critical internal applications, Experience with MLOps, including ML model deployment, monitoring, and lifecycle management, Familiarity with tools and platforms like MLflow, Kubeflow, or SageMaker, Experience with Snowflake, Airflow, and dbt, Experience with stream processing frameworks such as Flink, Experience with cloud-native infrastructure and containerized deployments, Experience with monitoring and observability tooling for production systems
What You'll Do.
Build and operate internal data platforms
and distributed workflow systems (Temporal
Write and maintain internal Python libraries (including shared Airflow operators and frameworks)
Build and operate Temporal-based workflow systems for long-running
reliable distributed data workflows
Build internal data platform applications
including config-driven UIs that enable users to author and run their own ingestion and transformation jobs
Own cost governance across Snowflake
and Kafka and other data platform services
and optimization initiatives
Administer Snowflake at depth: role hierarchy design
data masking and row access policies
Own production code end-to-end: design
and respond to incidents
Develop end-to-end automation for service and ML model deployment
ensuring smooth transition from development to production
Implement tools and processes to monitor the performance
and health of production systems and ML models
Support the Analytics Engineering function by building the platform capabilities (orchestration
metadata) that data marts are built on
How You'll Work.
Team & Collaboration
Work closely with software engineering, analytics, operations, business and product teams, to understand and meet their platform and data requirements
Full Job Description
About Ethos Ethos is a leading life insurance technology company on a mission to protect families by democratizing access to life insurance and empowering agents at scale. With its robust three-sided technology platform, Ethos is transforming the life insurance experience for consumers, agents, and carriers alike. Ethos offers instant, accessible products and a seamless online process that requires no medical exams and just a few health questions; it eliminates traditional barriers, making it easier than ever for everyone to protect their families. Ethos is redefining how life insurance is bought, sold, and underwritten. About the Role: Ethos is seeking a Data Engineer (IC3) to join our Data Platform team and build the internal infrastructure, services, and tooling that the rest of the company's data stack runs on. This is a software engineering role with a deep data background. You will design and operate distributed workflow systems on Temporal and Airflow, build internal platform applications (including config-driven UIs that let teams author and run their own ingestion and transformation jobs), and write Python libraries that other engineers across the company consume. You will also administer the data infrastructure we own, such as Snowflake, dbt Cloud, Airflow, and Kafka, with deep ownership of governance, reliability, and cost. Your customers are other engineers, analytics engineers, data scientists, and operations teams. The platform you build is what makes their work possible. If you enjoy building developer-facing platforms, operating distributed systems in production, and going deep on the modern data stack, we'd like to talk to you. Duties and Responsibilities: Build and operate internal data platforms, services, and distributed workflow systems (Temporal, Airflow) that the rest of the company's data stack runs on. Write and maintain internal Python libraries (including shared Airflow operators and frameworks) consumed by other engineering teams. Build a
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