Senior Data Engineer

📋 Description

• Own Data Platform Architecture: Design, build, and operate a production-grade data platform from
• Build Multi-Source Ingestion Pipelines: Develop concurrent ingestion systems for provider APIs
• Develop Batch and Event-Driven Workflows: Implement scheduled pipelines, historical backfills, and
• Ensure Reliable Failure Recovery: Implement retries, dead-letter queues, controlled replay
• Establish Raw-to-Curated Data Architecture: Preserve original source payloads, including provider
• Strengthen Data Quality and Governance: Define data contracts, automated validation rules, pipeline

🎯 Requirements

• Proven experience building production data platforms from the ground up, including architecture
• Hands-on production experience with Airflow, Dagster, Prefect, or Temporal, including workflow
• Practical production experience with Google Cloud Platform (GCP) and dbt, including data
• Experience developing asynchronous, event-driven systems using messaging platforms or task queues
• Strong Python skills, particularly asynchronous HTTP requests and concurrent processing using
• Advanced SQL knowledge and practical PostgreSQL experience, including data modeling, query

🎁 Benefits

• Fully remote work: Work remotely from eligible locations across Europe and Latin America, with
• Technical ownership: Lead the architecture and evolution of a data platform, with meaningful
• Modern technology stack: Work with Python, PostgreSQL, GCP, dbt, event-driven systems, workflow
• End-to-end impact: Build foundational infrastructure that directly supports product functionality
• Engineering autonomy: Take ownership of technical challenges and shape scalable solutions in a
• Innovation opportunities: Explore advanced data processing, entity resolution, external data