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Design and maintain a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows. Ensure data reliability through automated validation, monitoring, and robust failure handling across the entire data lifecycle.
Join a data engineering team building a platform that turns information from many sources into reliable, up-to-date company intelligence. You will own the platform end to end, from architecture and ingestion through production operations, supporting products with trusted data.
Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Build resilient intake from provider 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 event-driven processing with messaging or task queues, including retries, dead-letter queues, and controlled replay.
Preserve source payloads in Google Cloud Storage and transform them with dbt into raw, standardized, and curated data layers.
Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures.
Design and optimize PostgreSQL schemas and loading patterns for reliable downstream use.
Integrate data enrichment and LLM-based structured extraction into the platform.
At least 5 years building and operating production data platforms that ingest data from multiple sources, with ownership from architecture through ongoing operation.
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 tools such as asyncio, aiohttp, or HTTPX.
Strong SQL and PostgreSQL skills, including data modeling, query optimization, and incremental loading.
Experience with event-driven systems, queues, data contracts, raw and curated storage, retention, testing, and monitoring.
Experience building a platform or substantial pipelines from scratch is valued. Web scraping, entity resolution, enrichment, LLM-based extraction, and startup or small-team experience are also useful.
Base salary: $100,000 to $140,000 USD annually. Visa sponsorship is not available.
Fully remote for candidates based in Europe, including the United Kingdom, Iceland, Liechtenstein, Norway, Switzerland, and Ukraine.
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