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You will design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows. Additionally, you will own the platform end-to-end, from architecture and ingestion to production operations and data transformation.
Join a data infrastructure and analytics 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 to production operations, enabling trusted data for downstream products.
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 limits 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, 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.
At least 5 years building and operating production data platforms, integrating multiple sources from architecture through deployment and ongoing operations.
Production experience with workflow orchestration, including dependencies, retries, and failure recovery; Airflow experience is preferred.
Hands-on production experience with dbt and Google Cloud Platform.
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 incremental loading.
Experience with event-driven systems, messaging or task queues, and asynchronous failure recovery.
Experience with data contracts, raw and curated storage, retention policies, automated validation, pipeline testing, and monitoring.
Experience building platforms or substantial pipelines from scratch is valuable. Web scraping, entity resolution, LLM-based extraction, BigQuery, and Dataform experience are also useful.
Base salary: $100,000 to $140,000 USD annually. Visa sponsorship is not available.
Remote within Europe, including the United Kingdom, Norway, Switzerland, Iceland, Liechtenstein, and Ukraine.
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