Data Engineer – Data Platforms & AI Tooling (Remote, LATAM)

ITX is Hiring a Data Engineer – Data Platforms & AI Tooling!

Are you passionate about building the data foundations that power modern AI systems?

We're looking for a Data Engineer to join Data Platforms & Internal Tooling Projects. In this role, you'll help build the enterprise data platform that powers analytics, internal products, and our growing Agentic AI ecosystem.

This is not a traditional analytics-focused data engineering role. You'll work closely with AI, platform, and infrastructure teams to build the pipelines, data products, and integration layers that allow autonomous agents to securely access and use enterprise data in production.

If you're excited about combining modern data engineering with Agentic AI, cloud platforms, and large-scale systems, we'd love to hear from you.

Note: This role is limited to candidates based in LATAM. Candidates from other locations will not be considered for this role.

What You'll Do

- Build and maintain scalable batch and streaming data pipelines that ingest and transform data from applications, databases, APIs, event streams, and third-party systems.

- Develop trusted, reusable data products that support analytics, business applications, and AI solutions.

- Design and maintain data models that enable reporting, analytics, and AI consumption.

- Build AI-facing integration layers, including MCP servers and similar interfaces that allow AI agents to securely access data and platform capabilities.

- Collaborate with AI, platform, and infrastructure teams to support production-grade Agentic AI solutions.

- Implement data quality, testing, monitoring, observability, and lineage across data pipelines and AI integrations.

- Ensure data governance, privacy, security, and access-control standards are applied consistently.

- Prepare structured and unstructured data for analytics, machine learning, generative AI, and agentic workflows.

- Contribute to architecture decisions and help scale the organization's data platform for future growth.

What We're Looking For

Data Engineering Foundations

- 4+ years of experience in Data Engineering, Backend Engineering, or a related field.

- Strong Python and SQL skills.

- Experience building and operating production data pipelines.

- Experience with cloud data platforms such as Snowflake, Databricks, BigQuery, Redshift, Microsoft Fabric, or similar.

- Experience with dbt or comparable data transformation tools.

- Experience with orchestration tools such as Airflow, Dagster, Prefect, Databricks Workflows, Azure Data Factory, or similar.

- Experience with data modeling techniques such as dimensional modeling, SCDs, Data Vault, or comparable approaches.

- Experience working with at least one major cloud provider (Azure, AWS, or GCP).

Agentic AI Experience

- Experience supporting, integrating, or developing AI-powered and Agentic AI solutions in production environments.

- Familiarity with Retrieval-Augmented Generation (RAG) concepts, including embeddings, indexing, and retrieval workflows.

- Experience with vector databases such as Pinecone, Weaviate, Qdrant, pgvector, or similar technologies.

- Understanding of how AI agents consume data and interact with enterprise systems.

- Experience building MCP servers or comparable agent-tool integration patterns is highly valued.

- Familiarity with agent evaluation and observability tools such as Langfuse, LangSmith, Promptfoo, DeepEval, LiteLLM, or similar is a plus.

Platform Engineering & Operations

- Experience with CI/CD practices and version control workflows.

- Familiarity with Docker and containerized environments.

- Understanding of Infrastructure as Code (Terraform or similar tools).

- Experience implementing monitoring, telemetry, dashboards, and alerting for production systems.

- Familiarity with OpenTelemetry (OTel) and observability best practices is a plus.

Collaboration & Ways of Working

- Active use of AI-assisted development tools such as GitHub Copilo