Remote Data Engineer for ML/AI Data Platform

FEI Systems; Columbia (MD); On-site; USD 120,000 - 180,000; Full time

Job summary

FEI Systems is seeking a Data Engineer to support ML/AI initiatives in a cloud environment. You will work with the Solution Architect, Data Architect, DevOps, and Application Engineering teams to ensure high-quality, governed data for model training and deployment.

The role emphasizes Snowflake-based data engineering, pipeline development, and data quality, with growth into feature engineering and MLOps over time.

Qualifications

• 5+ years of hands-on data engineering experience in a cloud environment.
• Strong proficiency in Snowflake, Python, and SQL is required.
• Familiarity with AWS-native data services and data governance concepts.

Responsibilities

• Design, build, and maintain scalable data pipelines supporting ML/AI workloads.
• Engineer pipeline patterns including full loads, incremental loads, change-based loads, and SCDs.
• Ensure pipelines are reliable, secure, and maintainable within an AWS ecosystem.
• Perform data transformations in Snowflake using SQL and Snowflake features.
• Design schemas, tables, views, and materialized views for ML/AI use.
• Support AWS-native data lake patterns using S3, Glue, Athena, Iceberg, and S3 Tables.
• Perform data cleansing, normalization, and enrichment for ML model development.
• Implement feature engineering pipelines and ensure feature reuse across models.

Education

Bachelor's degree

Tools

Python

SQL

PostgreSQL

AWS

Apache Iceberg

S3 Tables

Kinesis

Kafka

Airflow

CI/CD

Data modeling

Data validation

Data lake

Job description

FEI Systems is seeking a Data Engineer to support ML/AI initiatives in a cloud environment. You will work with the Solution Architect, Data Architect, DevOps, and Application Engineering teams to ensure high-quality, governed data for model training and deployment.

The role emphasizes Snowflake-based data engineering, pipeline development, and data quality, with growth into feature engineering and MLOps over time.