AI Data Engineer
Remote AI Data Engineer designing cloud data and AI architecture on AWS, building data ingestion/transformation pipelines, and helping implement a new enterprise data platform including vector and graph data management. Core stack: CloudFormation, S3, Glue, Athena, Redshift, Lake Formation, SageMaker, plus Databricks.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Proven experience in AWS Cloud data architecture and AI solutions
- Strong knowledge of data integration, ingestion, and transformation tools
- Experience building scalable data platforms for enterprise ingestion, storage, and processing use cases
- Experience handling structured/unstructured, vector, and graph data
- Familiarity with data governance and security best practices in AWS
- Fluent in English (written and spoken)
Nice to have
- Spanish at an intermediate level
- Ecosystem experience with Lake Formation, SageMaker, and Databricks
Full description
Position: AI Data Engineer
Location: Remote
Language Requirements: Advanced English (required), Intermediate Spanish (desired)
About the Role
We are looking for an AI Data Engineer to support several initiatives within our Data Management team, focused on Artificial Intelligence, data processing, and cloud integration across our Amazon Web Services environments.
In addition, this role will help design and implement a new enterprise data platform to support multiple business units, focused on building scalable capabilities for data ingestion, storage, and processing. The ideal candidate will have solid experience designing and deploying cloud-based data and AI architectures, as well as developing robust data pipelines and supporting modern analytics and AI workloads.
Responsibilities
Design and implement cloud data and AI architecture solutions on AWS.
Develop and maintain data integration, ingestion, and transformation pipelines.
Support the design and implementation of a new centralized data platform for enterprise data ingestion, storage, and processing.
Manage structured and unstructured data, including vector and graph data administration.
Collaborate with cross-functional teams to ensure data quality, security, and availability.
Optimize data workflows and ensure scalability of deployed solutions.
Main Technologies
AWS Services: CloudFormation, S3, IAM, Glue, Athena, Synapse, Redshift, Lake Formation, SageMaker
Data Processing: ETL/ELT frameworks, data pipelines, data lake management
AI/ML Integration: vector databases, graph data models
Additional ecosystem experience is highly valued, especially with tools such as Lake Formation, SageMaker, and platforms like Databricks.
Requirements
Proven experience in AWS Cloud data architecture and AI solutions.
Strong knowledge of data integration, ingestion, and transformation tools.
Experience building scalable data platforms for enterprise ingestion, storage, and processing use cases.
Experience handling structured/unstructured, vector, and graph data.
Familiarity with data governance and security best practices in AWS.
Fluent in English (written and spoken).
Spanish at an intermediate level is a plus.