Data Engineer

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!

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 (Big Query, 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 Virtus Lab 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.