[Hiring] Staff Data Engineer at VirtusLab

We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself!

What we expect in general

Technical Leadership & System Design:

• Proven experience building web crawling or large-scale data systems from scratch.
• Strong architectural skills in designing scalable, fault-tolerant distributed systems.
• Track record leading complex technical initiatives and driving architecture direction for teams.
• Demonstrated ability to evolve production systems incrementally while maintaining reliability.
• Experience mentoring engineers at all levels and promoting a collaborative culture.

Data Engineering Expertise:

• Deep background in large-scale data engineering (terabytes daily).
• Hands-on experience with cloud data warehouses (BigQuery, Snowflake).
• Experience with Apache Kafka, Kubernetes (GKE/EKS), and orchestration tools (Airflow).
• Familiarity with multi-cloud environments (GCP + AWS).
• Expertise in designing and operating ETL/ELT pipelines.

Web Crawling & Data Extraction:

• Deep expertise in web crawling technologies and advanced scraping (Scrapy or similar).
• Experience in extracting structured/unstructured web data and SERP extraction.
• Knowledge of proxy infrastructure management, anti-bot detection, and ethical crawling.
• Familiarity with crawling vendors and AI/LLM-based extraction approaches.

Client Engagement & Advisory:

• Support the VirtusLab U.S. and international teams by lending senior technical expertise to client-facing activities, including technical discovery sessions, workshops, and solution architecture.
• Conduct requirements analysis and solution discovery, identifying business and technical needs.
• Provide technical consulting and advisory services, recommending appropriate data architectures aligned with customer goals.
• Prepare and review technical sections of commercial offers, including solution descriptions, statements of work (SoWs), project estimates, timelines, and delivery models.