Gen AI Data Engineering Analyst

Socket.dev; Georgia; On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Total Rewards Program

Job summary

American International Group, Inc. (AIG) is seeking an Analyst in the Gen AI Data Engineering team to design and operationalize cloud-native big data solutions enabling AI models and analytics.

You will collaborate across analytics, engineering, and data science teams to deliver scalable data platforms, learn through instructor-led masterclasses, and contribute to innovative AI initiatives in a hands-on, in-person environment.

Qualifications

• Bachelor’s degree or candidate for Bachelor’s degree in Computer Science, Engineering, Data, Math, or Statistics to be received no later than June 2027
• Strong background in data engineering and scalable data solutions in work or school settings
• Proficiency with cloud-native platforms and tools listed above
• Experience developing AI/ML models or hands-on desire to use AI platforms

Responsibilities

• Collaborating with stakeholders to identify and deliver innovative data solutions that meet evolving business needs
• Building and maintaining cloud-native big data solutions and Gen AI models
• Partnering with data architects and senior engineers to implement scalable designs
• Working with analytics, application development, and data science teams to drive innovation
• Delivering high-quality results on fast-paced schedules with rigorous development and code management standards

Skills

Data engineering

Cloud-native

PySpark

Spark SQL

Java/JavaScript/TypeScript

Communication

Analytical thinking

Collaboration

Education

Bachelor’s degree in CS/Engineering/Data/Math/Statistics

Tools

Hadoop

HDFS

Spark

Kubernetes

ElasticSearch

Palantir Foundry

Snowflake

AWS SageMaker

Job description

American International Group, Inc. (AIG) is seeking an Analyst in the Gen AI Data Engineering team to design and operationalize cloud-native big data solutions enabling AI models and analytics.

You will collaborate across analytics, engineering, and data science teams to deliver scalable data platforms, learn through instructor-led masterclasses, and contribute to innovative AI initiatives in a hands-on, in-person environment.