Data Engineer - ML/AI Data Platform (Remote)

At FEI Systems, we create innovative technology solutions to improve the delivery of health and human services because we know when cumbersome administrative processes stand in the way, those who need it most are often left without access to proper care and support. From comprehensive case management software to disaster recovery services and content management information systems used in delivering foreign aid, our solutions are improving the lives of millions of people. We’re looking for a data engineer who shares our commitment to leveraging technology to make a real impact in the world – a professional who knows, beyond all else, that the quality of our products and services is only as good as the company we keep.

All candidates will be required to complete at least one in-person interview as part of our hiring process.Role Overview

We are seeking a Data Engineer to support Machine Learning and AI initiatives. Working closely with the Solution Architect, Data Architect, DevOps, and Application Engineering teams, this role is responsible for ensuring that data within our cloud-based platform is high quality, well-governed, feature-ready, and production-grade to support model training, deployment, and ongoing operations.

The ideal candidate has 5+ years of cloud data engineering experience with strong proficiency in Snowflake, Python, and SQL, and solid familiarity with AWS-native data services.

Candidates are not expected to arrive with expertise across every area listed. We are looking for demonstrated strength in the core data engineering and Snowflake skills, combined with the initiative and aptitude to grow into the broader scope of the role.

Day-One Priorities & Scope

Immediate focus is Snowflake-based data engineering, pipeline development, and data quality. Feature engineering, model training support, and MLOps contributions are growth areas that will ramp over time as you become embedded with the team.

Key ResponsibilitiesData Pipeline Engineering

• Design, build, and maintain scalable data pipelines supporting ML/AI workloads.

• Engineer pipeline patterns including full loads, incremental loads, change-based loads, and slowly changing dimensions.

• Ensure pipelines are reliable, performant, secure, and maintainable, troubleshoot and monitor pipelines within an AWS ecosystem.

Snowflake & Cloud Data Engineering

• Perform data transformations in Snowflake using SQL and native Snowflake features.

• Design and optimize schemas, tables, views, and materialized views for ML/AI consumption.

• Support AWS-native data lake patterns using S3, Glue, Athena, Apache Iceberg, and S3 Tables.

Feature Engineering & Data Preparation