Data Collection Engineer

Role Description

Two Six Technologies is seeking a highly skilled Data Collection Engineer to design, scale, and maintain our distributed web scraping and data extraction infrastructure. In this role, you will be responsible for building resilient data pipelines that harvest data from complex web ecosystems, ensuring strict data quality through automated validation, and managing containerized workloads at scale.

• Distributed Crawler Development: Design and deploy high-performance, distributed web scrapers using Python and Scrapy to extract massive datasets efficiently.
• Dynamic Content Extraction: Utilize Browser Scripting tools to navigate, interact with, and extract data from modern, dynamic, and JavaScript-heavy websites.
• Infrastructure & Container Orchestration: Deploy, scale, and manage scraping workloads on Kubernetes, ensuring optimal resource allocation and fault tolerance.
• Data Validation & Quality Assurance: Define strict JSON Schemas and leverage Pydantic to enforce data types, validate incoming payloads, and catch data drift early.
• Data Ingestion & Storage: Build and optimize search and storage pipelines using Elasticsearch, transforming raw web dumps into highly structured, searchable data.
• Pipeline Workflow Management: Architect robust pipeline workflows to manage the end-to-end data lifecycle—from discovery and extraction to validation and storage.
• Anti-Bot & Proxy Engineering: Manage complex proxy rotation, session handling, and browser fingerprinting to maintain high success rates against advanced anti-scraping systems.

Qualifications

• 7+ years of professional software engineering experience, with a heavy focus on web scraping, data engineering, or distributed systems.
• Excellent reverse-engineering skills, with the ability to dissect network traffic, unearth hidden APIs, and bypass complex web barriers.
• A strong commitment to data integrity, system monitoring, and building self-healing scraping systems.
• Expert-level proficiency in Python.
• Deep experience with Scrapy and distributed scraping architectures (e.g., handling distributed queues, broad vs. deep crawling).
• Proven experience with browser automation tools (Playwright, Selenium, or Puppeteer).
• Mastery of JSON, JSON Schema, and data validation using Pydantic.
• Hands-on experience indexing, querying, and optimizing Elasticsearch clusters.
• Strong proficiency in managing and scaling applications within Kubernetes environments.
• Experience building structured pipeline workflows to handle complex, multi-stage data extraction tasks.

Requirements

• Bachelor’s degree in Computer Science, Engineering.

Benefits

• Medical, dental, and vision insurance.
• Life and disability insurance.
• Retirement benefits.
• Paid leave.
• Tuition assistance and professional development.