Dieses Stellenangebot ist nicht mehr verfügbar
Über
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) 464-4218.
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.
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot wurde von einem unserer Partner veröffentlicht. Sie können das Originalangebot einsehen hier.