Staff Data Engineer
Virtus Lab sp. z o.o. (Ltd.)
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. #J-18808-Ljbffr
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