Senior Data Engineer

About the Role Join a data and infrastructure team building a platform that turns information from multiple sources into reliable, current company intelligence. You will own the platform end to end, from ingestion and architecture to production operations, powering 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. Ingest data from APIs, webhooks, files, and web scraping with rate limits and robust failure handling. Orchestrate scheduled workflows and historical backfills using Airflow, Dagster, Prefect, or comparable tools. Build event-driven systems with messaging or task queues, including retries, dead-letter queues, and controlled replay. Store original payloads in Google Cloud Storage and transform data with dbt into raw, standardized, and curated layers. Implement idempotent upserts, data contracts, validation, pipeline tests, retention policies, and monitoring for freshness and failures. Design and optimize PostgreSQL schemas and loading patterns, and integrate data 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. 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 with raw and curated data storage, data contracts, retention, automated validation, pipeline testing, and monitoring. Web scraping, entity resolution, data enrichment, BigQuery, Dataform, and LLM-based extraction experience are useful. Experience building platforms from scratch or working in small, fast-moving teams is also valued. 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 residency is not required.