Staff Data Engineer

Serv is a global executive recruitment partner hiring for Mercator.ai, which is focused on building scalable data infrastructure for data-driven decision making. The Staff Data Engineer will lead the design and development of distributed data pipelines, ensuring scalability, reliability, and integration of modern tools to enhance engineering output.

Responsibilities:

• Lead the architecture and evolution of scalable, distributed data pipelines, ensuring high availability and performance at scale
• Design and implement robust data models to support reporting and advanced data applications
• Build and maintain distributed web scraping systems using tools such as Playwright, Selenium, and BeautifulSoup
• Develop systems capable of handling anti-scraping measures, proxy rotation, and high-volume data extraction
• Integrate AI and LLMs into engineering workflows for code generation, automation, and optimization
• Apply prompt engineering techniques to improve data processing, documentation, and troubleshooting
• Identify and implement system and process improvements to optimize performance and efficiency
• Manage and scale cloud-based data infrastructure, including data warehouses, object storage, and search systems
• Deploy and maintain containerized workloads using Kubernetes
• Implement data quality monitoring and governance processes to ensure accuracy and reliability
• Mentor junior engineers through code reviews, documentation, and knowledge sharing
• Communicate technical concepts clearly and provide business context for engineering decisions

Requirements:

• 5+ years of experience in Data Engineering with a track record of scaling systems
• Expert proficiency in Python and advanced SQL, including performance tuning and optimization
• Strong experience with workflow orchestration tools such as Airflow or Prefect and transformation tools such as dbt
• Proven experience building resilient web scraping systems using Playwright, Selenium, and BeautifulSoup
• Deep understanding of relational and NoSQL databases including Postgres, MongoDB, and ElasticSearch
• Experience working with large-scale data systems such as BigQuery
• Strong proficiency with CI/CD pipelines, Git, and Docker
• Experience designing and maintaining distributed systems with high availability and fault tolerance
• Experience with GCP or AWS and Kubernetes for infrastructure management
• Familiarity with LLMs such as ChatGPT, Claude, or Gemini for engineering workflows
• Experience with prompt optimization and AI-assisted development