Job Details

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 and execute enterprise Machine Learning and Artificial Intelligence initiatives. This role is a hands-on, tactical execution position focused on building, operating, and maintaining the data pipelines and data foundations required for ML/AI solutions.

Working closely with the ML/AI Architect, data scientists, and application engineering teams, this role is responsible for ensuring that data within our AWS and Snowflake-based data lake is high quality, well-governed, feature-ready, and production-grade to support model training, deployment, and ongoing operations.

Primary Responsibilities

Data Pipeline Engineering

• Design, build, and maintain scalable data pipelines to support ML/AI workloads
• Ingest data from multiple sources into the Snowflake data lake using batch and streaming patterns
• Develop and maintain ELT pipelines leveraging Snowflake-native capabilities
• Ensure pipelines are reliable, performant, and production-ready

Snowflake Data Engineering & Transformation

• Perform data transformations directly in Snowflake using SQL and Snowflake features
• Design and optimize schemas, tables, views, and materialized views for ML/AI consumption
• Implement transformation logic supporting analytics, feature engineering, and model training
• Optimize Snowflake usage for performance and cost efficiency

Data Quality, Governance & Management

• Implement data quality checks, validation rules, and monitoring within pipelines and Snowflake
• Support data governance initiatives including metadata management, lineage, and access controls
• Ensure datasets adhere to enterprise standards for security, privacy, and compliance
• Identify, troubleshoot, and remediate data quality issues impacting ML/AI workflows

Feature Engineering & Data Preparation

• Perform data cleansing, normalization, and enrichment to support ML model development
• Design and implement feature engineering pipelines, including feature aggregation and transformation
• Ensure consistency, reuse, and versioning of features across models and use cases
• Collaborate with ML engineers and data scientists to operationalize features from Snowflake into training pipelines

Model Training & Execution Support

• Support and execute model training workflows, including dataset preparation and refreshes
• Automate data preparation steps for experimentation, retraining, and scheduled runs
• Ensure training datasets and features are reproducible, traceable, and auditable

MLOps & SDLC Integration

• Integrate data pipelines and Snowflake transformations into CI/CD workflows
• Support version control, testing, and deployment of data assets
• Monitor pipeline health, data freshness, and downstream impacts on ML/AI systems
• Partner with platform, ML, and DevOps teams to improve operational maturity

Required Technical Skills

Data Engineering & Snowflake

• Strong proficiency in Python for data processing and pipeline development
• Advanced SQL skills, with hands-on experience transforming data in Snowflake
• Experience designing ELT pipelines using Snowflake as the central data lake
• Understanding of Snowflake performance tuning and cost optimization concepts

Cloud & AWS

• Experience working within the AWS ecosystem, including services such as:
• S3, Glue, Athena
• Lambda, Step Functions
• Kinesis, Snowpipe or MSK (preferred)
• Experience integrating Snowflake with AWS-based ingestion and processing pipelines
• Exposure to Amazon SageMaker data preparation and training workflows

ML/AI Data Foundations

• Understanding of data requirements for machine learning and AI workloads
• Experience preparing training datasets and features from enterprise data lakes
• Familiarity with reproducibility, dataset versioning, and data lineage concepts

DevOps & Engineering Practices

• Experience operating within a structured SDLC
• Familiarity with CI/CD pipelines for data and ML workflows
• Understanding of API-based and event-driven data integration patterns
• Experience supporting distributed data processing environments

Required Education/Certification

• Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or related field

Preferred Qualifications

• Experience supporting ML/AI platforms or products in production
• Familiarity with feature stores and ML data management tools
• Exposure to data observability, quality, and monitoring solutions
• Experience working in governance-heavy or regulated environments
• Snowflake or AWS certifications (preferred, not required)
• Experience leveraging ML/AI in a highly regulated healthcare environment (Understanding of HIPAA, 42CFR Part 2 and other privacy regulations)

What Success Looks Like

• Reliable, high-quality Snowflake datasets powering ML/AI use cases
• Well-governed, trusted data foundations for feature engineering and model training
• Efficient, repeatable data preparation and transformation workflows
• Reduced friction between data engineering, ML, and application teams

Location: Remote

Status: Full-time position with full company benefits

NOTICE: EO/AA/VEVRAA/Disabled Employer - Federal Contractor. FEI Systems participates in E-Verify, a federal program that enables employers to verify the identity and employment eligibility of all persons hired to work in the United States by providing the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee's Form I-9 to confirm work authorization. For more information on E-Verify, please contact DHS at (888) ###-####.

Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, marital status, political affiliation, disability, or genetic information, except where it relates to a bona fide occupational qualification or requirement. FEI Systems creates an Affirmative Action Plan on an annual basis. Pursuant to federal law, the portions of FEI Systems' Affirmative Action Program that relate to Section 503 (Persons with Disabilities) and/or Section 4212 (Protected Veterans), are available for inspection upon request by applicants and employees during FEI Systems' normal business hours.