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Open nowFirst seen 37 hours ago

AI Data Engineer

Inclusion Cloud110 open roles

Where
Remote
Work mode
Remote
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Your applicationOpen nowAI Data EngineerInclusion Cloud · Remote

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 37 hours ago

The posting

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.

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