Senior Data Engineer (Remote - Latin America)

A data and infrastructure team at a company that builds a platform turning information from many sources into reliable, current company intelligence. The engineer will own this platform end to end, from architecture and data ingestion through to production operations, supplying trusted data to downstream products.

What you'll do

• Design and build a multi-source data platform that supports concurrent ingestion, event-driven processing and orchestrated batch workflows.
• Ingest data from APIs, webhooks, files and web scraping, handling rate limits and failures robustly.
• Schedule workflows and historical backfills using orchestration tools such as Airflow, Dagster or Prefect.
• Build messaging and task queue flows with retries, dead-letter queues and controlled replay.
• Store raw payloads in cloud object storage and transform data with dbt into raw, standardized and curated layers.
• Implement idempotent upserts, data contracts, automated validation, pipeline tests and freshness and failure monitoring. Design and optimize PostgreSQL schemas and loading patterns, and add enrichment and LLM-based structured extraction.

What you need

• At least 5 years building and running production data platforms, with ownership from architecture through deployment and ongoing operations.
• Production experience with Google Cloud Platform, dbt and a workflow orchestrator such as Airflow, Dagster, Prefect or Temporal.
• Strong Python skills, including asynchronous HTTP and concurrent processing (asyncio, aiohttp or HTTPX).
• Strong SQL and PostgreSQL skills, including data modeling, query optimization and incremental loading.
• Experience with event-driven systems, messaging or task queues, and failure recovery.
• Must be based in Latin America to be eligible. Startup or small-team experience, web scraping, entity resolution, enrichment and LLM-based extraction are a plus.

Applicants must be based in: Brazil, Mexico, Colombia, Argentina, Chile, Peru.

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