About the Role
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.
What You’ll Do

• 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.

What We’re Looking For

• 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.

Compensation & Benefits
Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available.
Location
Fully remote for candidates 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, current company intelligence. You will own the platform end-to-end, from architecture and ingestion through production operations.
What You’ll Do

• 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.

What We’re Looking For

• 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.

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