Forward-Deployed Data Engineer for Gen AI Pipelines

Miami Neuroscience Institute Baptist Health South Florida; Florida; On-site; USD 120,000 - 180,000; Full time

Job summary

Sedgwick is seeking a Junior Forward Deployed Engineer to architect enterprise data pipelines powering AI initiatives. You will design, build, and optimize data flows across on-premise and multi-cloud environments (Snowflake, AWS, Azure), ensuring data quality and governance for model training and inference.

You will collaborate with Data Science, MLOps, and IT teams to translate evolving requirements into scalable, production-ready data solutions, while navigating enterprise constraints and

Qualifications

• Master's degree in Computer Science, Data Engineering, or a related field.
• Six (6) years of hands-on data engineering experience in multi-cloud environments or equivalent.
• Expert-level proficiency in Snowflake architecture and integration with cloud AI services.
• Mastery of Python, SQL, and PySpark; strong data orchestration and containerization (Docker).

Responsibilities

• Designs, builds, and maintains resilient ETL/ELT pipelines ingesting data from on-premise systems and cloud services to Snowflake and AI services.
• Develops and maintains feature stores and analytically optimized datasets for ML workflows.
• Engineers data pipelines for generative AI use cases, including data extraction and vectorization across AWS and Azure environments.
• Acts as a Snowflake power user and technical lead for compute and storage optimization.
• Implements data quality, validation, and observability frameworks to detect data drift and issues.
• Works with cross-functional teams to ensure reliable, multi-cloud data movement and governance.

Skills

Python

SQL

Data engineering

Machine Learning

Gen AI

Team collaboration

Problem solving

Education

Master's degree in Computer Science or related field

Tools

Snowflake

AWS

Azure Data Factory

Azure Synapse

Docker

Airflow

Job description

Sedgwick is seeking a Junior Forward Deployed Engineer to architect enterprise data pipelines powering AI initiatives. You will design, build, and optimize data flows across on-premise and multi-cloud environments (Snowflake, AWS, Azure), ensuring data quality and governance for model training and inference.

You will collaborate with Data Science, MLOps, and IT teams to translate evolving requirements into scalable, production-ready data solutions, while navigating enterprise constraints and