Integration Engineer (Databricks)

TL;DR

Integration Engineer (Databricks/Fullstack): Building and maintaining third-party data integrations for a Master Data Management platform with an accent on Spark Structured Streaming and API orchestration. Focus on developing end-to-end pipelines, backend services in FastAPI, and frontend configuration interfaces in React.

Location: Hybrid role based in Medellin, Colombia

Company

A Databricks-native platform that unifies master data, product data, and relationships into a single AI-ready foundation.

What you will do

• Design, build, and maintain end-to-end third-party data provider integrations from API contract to UI configuration.
• Develop PySpark Structured Streaming pipelines on Databricks to ingest and transform enriched data.
• Build Python/FastAPI services to orchestrate API calls, handle authentication, and manage rate limiting.
• Develop Node.js/React interfaces for customers to configure and monitor integrations.
• Act as the primary technical point of contact with third-party data vendors.
• Ensure system reliability by implementing idempotent retries, observable logging, and alerting.

Requirements

• 5+ years of experience in application development and data engineering.
• Strong Python skills and experience building production services with FastAPI.
• Practical PySpark experience, including Structured Streaming and Delta Lake.
• Proficiency in Node.js and modern JavaScript/TypeScript (React preferred).
• Proven track record of integrating REST APIs, including OAuth and webhook handling.
• English: Excellent written and verbal communication skills required.

Nice to have

• Experience with enterprise data enrichment providers like Dun & Bradstreet or ZoomInfo.
• Knowledge of Master Data Management (MDM) and entity resolution.
• Familiarity with Databricks Unity Catalog, Workflows, and Jobs.
• Experience with Azure or AWS and CI/CD pipelines (Docker, Terraform).