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You will design and own a multi-source data platform, managing everything from ingestion and event-driven processing to orchestrated batch workflows. Your role involves building robust data pipelines, ensuring data quality through contracts and testing, and optimizing storage and transformation layers.
Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, current company intelligence. You will own the platform across architecture, ingestion, and production operations, supporting products with trusted data.
Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Build ingestion from provider APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.
Orchestrate scheduled workflows and historical backfills using Airflow, Dagster, Prefect, or similar tools.
Develop event-driven processing with messaging or task queues, including retries, dead-letter handling, and controlled replay.
Preserve source 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, validation, pipeline tests, and monitoring for freshness and failures.
Optimize PostgreSQL schemas and loading patterns, and integrate enrichment and LLM-based structured extraction.
At least 5 years building and operating production data platforms that integrate multiple sources, with ownership from architecture through deployment and ongoing operations.
Production experience with workflow orchestration, including dependencies, retries, and recovery; Airflow is preferred.
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, messaging or task queues, data contracts, raw and curated storage, retention policies, automated testing, and pipeline monitoring.
Experience building platforms or substantial pipelines from scratch is valuable. Web scraping, entity resolution, BigQuery, Dataform, and LLM-based extraction are also relevant.
Base salary: $100,000 to $140,000 USD annually. Visa sponsorship is not available.
Remote within Europe, including Norway, Switzerland, and the United Kingdom.
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