Data Engineer – Data Platforms, AI Tooling

This is a fully remote position, open to applicants in Latin America.

📋 Description

• Construct and manage scalable batch and streaming data pipelines sourced from applications, databases, APIs, event streams, and external systems.

• Create reliable, reusable data products intended for analytics, business applications, and AI solutions.

• Design and oversee data models tailored for reporting, analytics, and AI utilization.

• Develop AI-oriented integration layers, including MCP servers and similar interfaces.

• Collaborate with teams focused on AI, platform, and infrastructure to deliver production-grade Agentic AI solutions.

• Enforce data quality, testing, monitoring, observability, and lineage across all pipelines and AI integrations.

• Implement data governance, privacy, security, and access control protocols.

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

• Contribute to architectural decisions and enhance the scalability of the organization's data platform.

⛳️ Requirements

• A minimum of 4 years of experience in Data Engineering, Backend Engineering, or a related discipline.

• Proficiency in Python and SQL.

• Proven experience in constructing and managing production data pipelines.

• Familiarity with cloud data platforms such as Snowflake, Databricks, BigQuery, Redshift, Microsoft Fabric, or similar tools.

• Experience with dbt or similar data transformation solutions.

• Knowledge of orchestration tools including Airflow, Dagster, Prefect, Databricks Workflows, Azure Data Factory, or comparable options.

• Experience in dimensional modeling, SCDs, Data Vault, or other relevant methodologies.

• Proficient with at least one major cloud service provider: Azure, AWS, or GCP.

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

• Familiarity with RAG concepts, embeddings, indexing, and retrieval processes.

• Experience with vector databases like Pinecone, Weaviate, Qdrant, pgvector, or comparable technologies.

• Understanding of how AI agents process data and interact with enterprise systems.

• Experience with CI/CD methodologies and version control practices.

• Familiarity with Docker and containerized solutions.

• Knowledge of Infrastructure as Code principles, such as Terraform.

• Experience in implementing monitoring, telemetry, dashboards, and alerts for production systems.

• Active use of AI-assisted development tools like GitHub Copilot, Cursor, Claude Code, or similar resources.

• Exceptional communication and collaboration abilities.

• Capacity to work effectively with cross-functional engineering, platform, data, and AI teams.

• Comfortable operating within an Agile Kanban framework.

• Proficient in professional English.

🏝️ Benefits

• Competitive salary based on market standards relative to the candidate’s location.

• Automatic annual salary adjustments when market benchmarks exceed current compensation.

• Regular compensation reviews for team members.

• Commitment to fair and equitable pay practices.

• Full-time employment status.