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Sr Associate Data Engineer – Generative AI

Salary

$0.092k - $0.152k

Min Experience

2 years

Location

Hartford, CT

JobType

full-time

About the job

Info This job is sourced from a job board

About the role

Travelers provides insurance coverage to protect the things that are important to you. As a Senior Associate Data Engineer, you will help guide growth and transformation of our analytics landscape by designing, building, and deploying data solutions and APIs that support AI-driven solutions across global operations. Responsibilities Build and operationalize data solutions, correct problems, apply transformations, and recommend data cleansing/quality solutions. Participate in the design of data solutions. Analyze sources to determine value and recommend data to include in analytical processes. Incorporate core data management competencies including data governance, data security and data quality. Partner and collaborate with team and business users to support delivery and educate end users on data products/analytic environment. Perform data and system analysis, assessment and resolution for defects and incidents of moderate complexity and correct as appropriate. Test data movement, transformation code, and data components. Support implementation of vector database systems and embedding pipelines Assist in developing and maintaining RAG-based applications Perform other duties as assigned. Qualification Represents the skills you have Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise. Data Engineering Large Language Models (LLMs) REST API design Cloud infrastructure (AWS) Python programming Data preparation for AI/ML Vector databases Data security fundamentals Snowflake fundamentals SQL proficiency Agile methodologies Basic prompt engineering RAG architectures FastAPI Flask API documentation AI governance principles Basic LLM integration Container basics (Docker) Basic infrastructure automation Monitoring Logging tools API deployment Vector embedding concepts Batch processing systems Data warehouse concepts Data modeling ETL tools RESTful service integration Version control (Git) Required Bachelor's degree in Computer Science or related field 2+ years of data engineering or equivalent experience Technical expertise in understanding of Large Language Models (LLMs) Basic prompt engineering concepts Exposure to vector databases Data preparation for AI/ML models Understanding of RAG architectures REST API design and development Experience with FastAPI or Flask API documentation and testing Data security fundamentals AI governance principles Cloud infrastructure experience: AWS services (especially S3, Lambda, API Gateway) Basic LLM integration Container basics (Docker) Basic infrastructure automation Monitoring and logging tools API deployment and management Data processing and storage: Snowflake fundamentals Vector embedding concepts Batch processing systems Data warehouse concepts Data modeling ETL tools and frameworks RESTful service integration Development practices: Python programming SQL proficiency Version control (Git) Basic CI/CD concepts API testing frameworks Documentation (OpenAPI/Swagger) Agile methodologies Exposure to AI/ML projects Experience building and maintaining REST APIs Strong analytical and problem-solving skills Good communication abilities Ability to work in a team environment Basic understanding of international data protection regulations Willingness to collaborate across time zones

About the company

Travelers provides insurance coverage to protect the things that are important to you – your home, your car, your valuables and your business.

Skills

data engineering
large language models (llms)
rest api design
cloud infrastructure (aws)
python programming
data preparation for ai/ml
vector databases
data security fundamentals
snowflake fundamentals
sql proficiency
agile methodologies
basic prompt engineering
rag architectures
fastapi
flask
api documentation
ai governance principles
basic llm integration
container basics (docker)
basic infrastructure automation
monitoring
logging tools
api deployment
vector embedding concepts
batch processing systems
data warehouse concepts
data modeling
etl tools
restful service integration
version control (git)