About the Role
Join a data infrastructure and analytics team building a platform that turns information from many 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 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 using Airflow, Dagster, Prefect, or similar tools.

• Build event-driven systems with messaging or task queues, including retries, dead-letter queues, and controlled replay.

• Preserve original payloads in Google Cloud Storage and transform them with dbt into raw, standardized, and curated layers.

• Implement idempotent upserts and safe retries to prevent duplicate records and data corruption.

• Define 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, from architecture through ongoing operations.

• Production experience with workflow orchestration, including dependencies, retries, and failure recovery. Airflow is preferred; Dagster, Prefect, Temporal, or comparable tools are relevant.

• Hands-on production experience with dbt and Google Cloud Platform.

• Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, HTTPX, or similar tools.

• Strong SQL and PostgreSQL skills, including data modeling, query optimization, and incremental loading.

• Experience with event-driven systems, messaging or task queues, asynchronous processing, and recovery from failures.

• Experience implementing data contracts, raw and curated storage, retention policies, automated validation, pipeline tests, and monitoring.

• Web scraping, entity resolution, data enrichment, BigQuery, or Dataform experience is helpful, as is building platforms from scratch in a small team.

Compensation & Benefits
Base salary: $120,000 to $160,000 annually. Visa sponsorship is not available.
Location
Remote within the United States. New York-based candidates are welcome, but New York residence is not required.

About the Role
Join a data infrastructure and analytics team building a platform that turns information from many 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 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 using Airflow, Dagster, Prefect, or similar tools.

• Build event-driven systems with messaging or task queues, including retries, dead-letter queues, and controlled replay.

• Preserve original payloads in Google Cloud Storage and transform them with dbt into raw, standardized, and curated layers.

• Implement idempotent upserts and safe retries to prevent duplicate records and data corruption.

• Define 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, from architecture through ongoing operations.

• Production experience with workflow orchestration, including dependencies, retries, and failure recovery. Airflow is preferred; Dagster, Prefect, Temporal, or comparable tools are relevant.

• Hands-on production experience with dbt and Google Cloud Platform.

• Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, HTTPX, or similar tools.

• Strong SQL and PostgreSQL skills, including data modeling, query optimization, and incremental loading.

• Experience with event-driven systems, messaging or task queues, asynchronous processing, and recovery from failures.

• Experience implementing data contracts, raw and curated storage, retention policies, automated validation, pipeline tests, and monitoring.

• Web scraping, entity resolution, data enrichment, BigQuery, or Dataform experience is helpful, as is building platforms from scratch in a small team.

Compensation & Benefits
Base salary: $120,000 to $160,000 annually. Visa sponsorship is not available.
Location
Remote within the United States. New York-based candidates are welcome, but New York residence is not required.