Senior Data Platform Engineer - AI & ML Pipelines

Devoted Health Services; United States; On-site; USD 131,000 - 200,000; Full time

Benefits offered by this job

Health, dental and vision plans

Generous paid time off

Stock options

Job summary

Devoted Health is seeking a Senior Data Platform Engineer to design, build, and maintain scalable data infrastructure powering analytics, ML, and AI initiatives. You’ll work with Snowflake, Airflow, dbt, Kubernetes, Terraform, and Go/Python to enable data scientists and engineers.

The role emphasizes performance, reliability, and maintainability, with collaboration across teams and a focus on evolving the semantic layer and data agent.

Qualifications

• 5+ years working as an individual technical contributor.
• 5+ years' experience with data platforms.
• Experience with Cloud Data Warehouses (Snowflake, BigQuery, Redshift, etc.).
• Experience developing in Python or Go.
• Experience with a Workflow Orchestrator (Airflow, Luigi, Dagster, Prefect, etc.).

Responsibilities

• Design, develop and maintain a robust, scalable data platform that serves analytics, machine learning, and AI workloads.
• Build and evolve the infrastructure behind our Semantic Layer and Data Agent, including how LLMs discover, understand, and safely query our data.
• Establish evaluation, observability, and quality practices for AI systems that depend on the data platform, so we can measure accuracy and catch regressions.
• Collaborate with Data Science and Product Engineering on tooling to develop and deploy reliable data and AI products.
• Ensure data availability, quality, and reliability in the data platform.
• Identify areas for improvement with the platform.
• Propose new/improved solutions and lead them from design to implementation.
• Develop best practices for data modelling, pipelines, and testing.

Skills

Python

Go

Data Platform Design

Data Modeling

Tools

Snowflake

Airflow

dbt

Kubernetes

Terraform

Job description

Devoted Health is seeking a Senior Data Platform Engineer to design, build, and maintain scalable data infrastructure powering analytics, ML, and AI initiatives. You’ll work with Snowflake, Airflow, dbt, Kubernetes, Terraform, and Go/Python to enable data scientists and engineers.

The role emphasizes performance, reliability, and maintainability, with collaboration across teams and a focus on evolving the semantic layer and data agent.