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You will design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows. Additionally, you will own the platform end-to-end, from architecture and ingestion through production operations.
Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, up-to-date company intelligence. You will own the platform end to end, from architecture and ingestion through production operations, supporting products with trusted data.
Design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Ingest data from provider APIs, webhooks, files, and web scraping, with rate limiting and robust failure handling.
Orchestrate scheduled workflows and historical backfills with tools such as Airflow, Dagster, or Prefect.
Build event-driven systems with messaging and task queues, including retries, dead-letter queues, and controlled replay.
Preserve original payloads in cloud storage and transform them with dbt into raw, standardized, and curated layers.
Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures.
Design and optimize PostgreSQL schemas and loading patterns, and integrate enrichment providers and LLM-based structured extraction.
At least 5 years building and operating production data platforms that integrate multiple sources, with ownership from architecture through deployment and ongoing operations.
Production experience with dbt and Google Cloud Platform, plus workflow orchestration using Airflow, Dagster, Prefect, Temporal, or a comparable tool. Airflow experience is preferred.
Strong Python skills, including asynchronous HTTP and concurrent processing with tools such as asyncio, aiohttp, or HTTPX.
Strong SQL and PostgreSQL skills, including data modeling, query optimization, and reliable incremental loading.
Experience building event-driven systems with messaging or task queues, asynchronous processing, and failure recovery.
Experience with raw and curated storage, retention policies, data validation, pipeline testing, and monitoring.
Startup or small-team experience and broad ownership are valuable. Web scraping, entity resolution, data enrichment, LLM-based extraction, BigQuery, and Dataform experience are also useful.
Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available.
Remote, candidates must be based in Latin America.
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