Role overview

Data Engineer – Web Scraping, LLM Pipelines and Scalable Data Infrastructure

Requirements and responsibilities

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Key Responsibilities:

  • Build new structured datasets, including scraping accelerators, Form D filings and dynamic web sources.
  • Develop automated ETL pipelines that parse, clean and transform content using LLMs.
  • Define and maintain database schemas in Supabase or PostgreSQL.
  • Create evaluation frameworks to measure and compare LLM performance across pipeline components.
  • Contribute to the design of scalable data architectures using GCP services.
  • Improve reliability, observability and deployment workflows for scraping and data processing systems.

Requirements:

  • 4+ years of experience building data pipelines, backend services and automated data processing systems.
  • Strong background in web scraping with tools like Scrapy, Playwright or similar.
  • Experience deploying pipelines on cloud platforms such as GCP or AWS.
  • Solid knowledge of ETL frameworks, workflow orchestration (Airflow) and modern data stores (BigQuery, PostgreSQL).
  • Comfortable working with Docker and API frameworks like FastAPI.
  • Clear, fluent communication in English.
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Browse stack
FocusData EngineeringRole area
Seniority signalMiddleCandidate level
StackAWS, Docker, GCPPrimary skills
Location1 accepted countryEligibility

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