About this role

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.

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.

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

Key skills