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You will design and own a multi-source data platform, managing everything from architecture and ingestion to production operations. Responsibilities include building robust data pipelines, orchestrating workflows, and implementing data quality monitoring.
Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, current company intelligence. You will own the platform end-to-end, from architecture and ingestion through production operations.
Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Build intake pipelines for APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.
Orchestrate scheduled workflows and historical backfills using tools such as Airflow, Dagster, or Prefect.
Develop messaging and task queue systems with retries, dead-letter queues, and controlled replay.
Preserve source payloads in Google Cloud Storage and transform data 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 and LLM-based structured extraction.
At least 5 years building and operating production data platforms across multiple sources, with ownership from architecture through deployment and ongoing operations.
Hands-on production experience with dbt and Google Cloud Platform, and workflow orchestration using Airflow, Dagster, Prefect, Temporal, or a comparable tool. Airflow is preferred.
Strong Python skills, including asynchronous HTTP and concurrent processing with 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 data contracts, raw and curated storage, retention policies, automated testing, and production monitoring.
Helpful experience includes web scraping, entity resolution, company and people data enrichment, LLM-based extraction, and building platforms from scratch in small teams.
Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available.
Fully remote for candidates based in Latin America.
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