Data Engineer - ML/AI Data Platform (Remote)

Role Overview

FEI Systems is hiring a Data Engineer to support Machine Learning and AI initiatives. You will work closely with Solution Architects, Data Architects, DevOps, and Application Engineering to ensure data in a cloud platform is high quality, well-governed, feature-ready, and production-grade for model training, deployment, and operations.

Day-One Priorities

• Snowflake-based data engineering
• Pipeline development
• Data quality

Responsibilities

• Data Pipeline Engineering
  • Design, build, and maintain scalable pipelines for ML/AI workloads
  • Implement pipeline patterns: 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 transformations in Snowflake using SQL and native features
  • Design/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
  • Build data cleansing, normalization, and enrichment for ML development
  • Create feature engineering pipelines (aggregation and transformation)
  • Ensure feature consistency, reuse, and versioning across models and use cases
  • Support feature store patterns for feature discoverability and reuse
  • Collaborate with ML engineers/data scientists to operationalize features into training pipelines
• Model Training & MLOps Support
  • Support model training workflows (dataset preparation, scheduled refreshes)
  • Ensure training datasets/features are reproducible, traceable, and auditable
  • Integrate data pipelines into CI/CD workflows for version control, testing, and deployment of data assets
  • Monitor pipeline health, data freshness, and downstream ML/AI impact

Required Skills & Experience

• 5+ years hands-on cloud data engineering experience
• Python (strong proficiency for data processing and pipeline development)
• SQL (advanced; hands-on Snowflake transformation experience)
• Snowflake (ELT pipeline design, schema optimization, performance tuning, cost management)
• PostgreSQL (querying, data modeling, analytics); familiarity with SQL Server to PostgreSQL migration

Notes

• Candidates must complete at least one in-person interview as part of the hiring process.