🕒 yesterday
Own the end-to-end data platform, designing multi-source ingestion, event-driven processing, and orchestrated workflows while ensuring reliable storage, transformation, validation, and production operations.
Senior Data Engineer, LATAM
🕒 yesterday
PythonSQLPostgreSQLDbt
📜 Description
- Design a multi-source 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 queues with retries, dead-letter queues, and controlled replay.
- Store source payloads in Google Cloud Storage and transform data with dbt into raw, standardized, and curated layers.
- Implement data contracts, validation, pipeline tests, monitoring, optimized PostgreSQL loading, and enrichment with LLM-based extraction.
🛠️ Requirements
- 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.
✨ Benefits
- Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available.
Full job description
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.
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