🕒 yesterday
Own the end-to-end data platform, designing multi-source ingestion and event-driven workflows, building reliable transformation pipelines, and operating production data infrastructure.
Senior Data Engineer
🕒 yesterday
PythonSQLPostgreSQLDbt
📜 Description
- Design and build a multi-source platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
- Ingest provider APIs, webhooks, files, and scraped data with rate limiting and robust failure handling.
- Orchestrate scheduled workflows and historical backfills; build messaging and task-queue systems with retries, dead-letter queues, and replay.
- Preserve source 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 freshness and failure monitoring.
- Optimize PostgreSQL schemas and loading patterns, and integrate enrichment and LLM-based structured extraction.
🛠️ Requirements
- At least 5 years building and operating production data platforms across multiple sources, from architecture through 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 implementing data contracts, raw and curated storage, retention policies, automated validation, pipeline tests, and monitoring.
- Web scraping, entity resolution, data enrichment, BigQuery, or Dataform experience is helpful, as is building platforms from scratch in a small team.
✨ Benefits
- Base salary: $120,000 to $160,000 annually. Visa sponsorship is not available.
Full job description
About the Role
Join a data infrastructure and analytics team building a platform that turns information from many sources into reliable, current company intelligence. You will own the platform end to end, from architecture and ingestion through production operations.
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 provider APIs, webhooks, files, and web scraping, with rate limiting and robust failure handling.
Orchestrate scheduled workflows and historical backfills using Airflow, Dagster, Prefect, or similar tools.
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 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, automated 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.
What We're Looking For
At least 5 years building and operating production data platforms across multiple sources, from architecture through 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 implementing data contracts, raw and curated storage, retention policies, automated validation, pipeline tests, and monitoring.
Web scraping, entity resolution, data enrichment, BigQuery, or Dataform experience is helpful, as is building platforms from scratch in a small team.
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 residence is not required.
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