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

itx-jordan; Buenos Aires; Remote; ARS 91,841,000 - 134,359,000; Full time

Job summary

ITX is seeking a Data Engineer to join Data Platforms & AI Tooling, building scalable data pipelines, data products, and models powering analytics and autonomous AI systems.

You will collaborate with AI, platform, and infrastructure teams to deploy production data pipelines, governance, and data models, enabling secure, enterprise-grade data access. LATAM-based, remote work options available.

Qualifications

• 4+ years 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, 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).

Responsibilities

• Build and maintain scalable batch and streaming data pipelines ingesting data from applications, databases, APIs, and events.
• Develop trusted, reusable data products that support analytics and AI solutions.
• Design and maintain data models enabling reporting, analytics, and AI consumption.
• Build AI-facing integration layers and secure data access for agents.
• Collaborate with AI, platform, and infrastructure teams for production-grade solutions.
• Implement data quality, testing, monitoring, observability, and lineage across pipelines.
• Ensure data governance, privacy, security, and access-control standards are applied.
• Prepare structured and unstructured data for analytics, ML, and agentic workflows.
• Contribute to architecture decisions and scale the data platform for growth.

Skills

Python

SQL

Data pipelines

Cloud platforms

dbt

Airflow

Data modeling

Cloud provider experience

English proficiency

Tools

Snowflake

Databricks

BigQuery

Redshift

Microsoft Fabric

dbt

Airflow

Dagster

Prefect

Databricks Workflows

Azure Data Factory

Pinecone

Weaviate

Qdrant

pgvector

Job description

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 Copilot, Cursor, Claude Code, or similar.
• Excellent communication and collaboration skills.
• Ability to work effectively with cross-functional engineering, platform, data, and AI teams.
• Comfortable working in a fast-paced Agile (Kanban) environment.
• Professional English proficiency.

ITX’s Compensation Philosophy

Equality in compensation has been our practice since ITX started in 1997.

ITX believes that market-based pay ensures fair and equitable compensation for our worldwide team members and pay that is based on the market, not on who has the best negotiation skills. At ITX, you’ll never discover that someone in the same job with the same experience makes more than you, or that there are pay gaps based on race, gender, disability, or age.

How do our team members experience market-based pay at ITX? We gather market data to benchmark each position in our candidates’ and team members’ locations and use these benchmarks for candidate offers and to perform regular compensation reviews for our team members. You’ll never have to worry about asking for a pay raise again. At least once a year ITX automatically adjusts pay when the benchmark is higher than our team member’s compensation.

In LATAM the pay range for the Senior Software Engineer (Data Platforms & AI Tooling) role is $5,400 to $7,900 monthly, depending on experience, specific skills and certifications, and education. Based on your location in LATAM pay ranges could be adjusted according to local market data, which can vary from country to country. This variation percentage could be 16% lower or 14% higher.

Do you have questions about ITX’s compensation practices? Let us know! We’re proud of how we do compensation at ITX and welcome the opportunity to share more.

This role was posted by ITX on August 11, 2026.