About the Role
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.
What You’ll Do

• 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.

What We’re Looking For

• 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.

Compensation & Benefits
Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available.
Location
Remote, candidates must be based in Latin America.

About the Role
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.
What You’ll Do

• 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.

What We’re Looking For

• 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.

Compensation & Benefits
Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available.
Location
Remote, candidates must be based in Latin America.