Senior Data Engineer

About the Role

Join a data infrastructure 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, helping power downstream 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.
• Develop intake pipelines for provider APIs, webhooks, files, and web scraping, with rate limiting and robust failure handling.
• Orchestrate scheduled workflows and historical backfills using tools such as Airflow, Dagster, or Prefect.
• 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 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 providers and LLM-based structured extraction.

What We're Looking For

• At least 5 years building and operating production data platforms, with ownership spanning architecture, implementation, deployment, and ongoing operations.
• Production experience with GCP and dbt, plus workflow orchestration such as Airflow, Dagster, Prefect, or Temporal, including dependency management, retries, and recovery.
• Strong Python skills, including asynchronous HTTP and concurrent processing with tools such as asyncio, aiohttp, or HTTPX.
• Strong SQL and PostgreSQL skills in data modeling, query optimization, and reliable incremental loading.
• Experience with event-driven systems, queues, data contracts, raw and curated storage, retention policies, automated testing, and pipeline monitoring.
• Experience in a startup or small engineering team is useful. Web scraping, entity resolution, company or people data enrichment, and LLM-based extraction are also relevant.