Sr. Data Platform Engineer - GP, Remote: Colombia - Costa Rica, Fulltime

- This position is open to candidates located in Colombia or Costa Rica only -

We are looking for a Senior Data Platform Engineer to work with an AI-enabled platform supports operations, tracking and decision-making to optimize large-scale renewable and traditional energy portfolios. We're looking for an autonomous data engineer tostrengthen our data foundation through good modeling, clean schemas, reliability and automation.

Responsibilities

• Work closely with product teams to help define and execute technical criteria
• Architect and maintain robust data ingestion pipelines that feed both our application and analytics
• Design well-modeled, layered tables with clean schemas that turn raw data into analytics-ready data
• Help onboard client data from a variety of sources, such as Databricks via Delta Sharing, and integrate it with our existing services and workflows
• Make pipelines reliable and automated: data quality tests, monitoring, safe reprocessing and schema change handling
• Build a documented, well-tested data foundation that serves the app, analytics and future AI use cases

Technical requirements

• 5+ years of data engineering experience owning the design of production data pipelines end to end, workingas an autonomous IC.
• Designing and building production ingestion pipelines from APIs, files and shared-data sources, using a workflow orchestrator (any tool, e.g. Airflow, Dagster or Step Functions).
• Production experience with a cloud data warehouse (Snowflake preferred).
• Strong SQL, plus production experience in Python (preferred) or Node.js/TypeScript.
• AWS or another enterprise cloud platform.
• AI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows across a team and into the development lifecycle, including CI/CD.
• Strong English and communication skills.

Bonus Skills

• dbt
• Preparing data for AI/LLM use (e.g. semantic layers, metadata, retrieval-ready datasets)
• Infrastructure as code (e.g. Terraform)
• Exposure to energy, utilities or sustainability data