Engineer – Gen AI

Sedgwick

. Design, build, and maintain resilient ETL/ELT pipelines ingesting on-premise systems, AWS services, and Azure platforms for Snowflake and downstream AI services .

Posted 9/21/2026full-timeRemote • Tennessee • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining ETL/ELT pipelines across multi-cloud environments, with a strong focus on Snowflake architecture and data orchestration. Proficient in implementing automated data quality frameworks and collaborating with cross-functional teams to deliver scalable data solutions for AI and machine learning applications.

Highest-signal resume keywords

Snowflake Architecture ExpertiseAWS Data Services (S3, Glue, Lambda)Azure Data Services (Data Factory, Synapse)Python, SQL, and PySpark MasteryData Orchestration and Containerization (Docker)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT Pipeline DesignData ModelingData Quality AutomationFeature EngineeringGenerative AI Data ProcessingData Extraction from Legacy SystemsPerformance TuningCompute and Storage OptimizationVectorization and Embedding PipelinesCross-Platform Workflow Management

Soft Skills

Team CollaborationStress ManagementMultitaskingDeadline Management

Tools & Technologies

AirflowAWS Step FunctionsAzure Data FactorySnowpipeVector Databases

Certifications & Qualifications

Master’s Degree in Computer Science or Data Engineering

Industry Keywords

Data EngineeringMachine LearningAI ServicesMulti-Cloud EnvironmentsData Orchestration

Tech Stack

Tools & technologies

AirflowAWSAzureCloudDockerETLPySparkPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain resilient ETL/ELT pipelines ingesting on-premise systems, AWS services, and Azure platforms for Snowflake and downstream AI services
Develop and maintain feature stores and analytically optimized datasets for machine learning workflows
Engineer pipelines for generative AI use cases, including extraction, transformation, chunking, and loading of structured and unstructured data into vector databases
Serve as a Snowflake power user and technical lead, implementing data modeling, Snowpipe automation, and compute and storage optimization
Execute non-invasive data extraction from legacy systems while preserving system stability
Design and manage cross-platform workflows using Airflow, AWS Step Functions, and Azure Data Factory
Partner with IT, database, infrastructure, and security teams to resolve connectivity and access challenges and secure production approval for integrations
Implement automated data quality, validation, and observability frameworks
Optimize storage, compute usage, and query performance across Snowflake, AWS, and Azure
Partner with MLOps, Data Science, and AI teams to translate experimental use cases into scalable, production-ready data solutions
Perform other duties as assigned

Requirements

What you’ll need

Master’s degree in Computer Science, Data Engineering, or a related field from an accredited college or university preferred
Six (6) years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments or equivalent combination of education and experience required
Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and integration with external cloud AI services
Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services
Mastery of Python, SQL, and PySpark
Deep experience with data orchestration and containerization (Docker)
Proven ability to interface with on-premise SQL, Mainframe extracts, and flat files and transform them for modern cloud consumption
Strong understanding of Machine Learning data needs, including feature engineering
Strong understanding of Generative AI data needs, including vectorization and embedding pipelines
Ability to work in a team environment
Ability to meet or exceed Performance Competencies
Ability to handle work-related stress and multiple priorities simultaneously and meet deadlines
Travel as required

Benefits

Comp & perks

Work-life balance
Reasonable accommodations when applicable and appropriate
Equal Opportunity Employer
Drug-Free Workplace