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

• End-to-End Data Engineering Experience: Proven experience building production data platforms from
• Workflow Orchestration: Hands-on production experience with Airflow, Dagster, Prefect, or Temporal
• Google Cloud and dbt: Practical production experience with Google Cloud Platform (GCP) and dbt
• Event-Driven Architecture: Experience developing asynchronous, event-driven systems using messaging
• Python Programming: Strong Python skills, particularly asynchronous HTTP requests and concurrent
• SQL and PostgreSQL: Advanced SQL knowledge and practical PostgreSQL experience, including data

🎁 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