Senior Data Platform Engineer

Job description

## About Hexnode Hexnode is a global leader in Unified Endpoint Management (UEM), trusted in over 100 countries and managing millions of devices worldwide. With continuous innovation across Apple, Windows, Android, macOS, Linux, and tvOS ecosystems, Hexnode is redefining enterprise mobility and cybersecurity. As we expand our Extended Detection and Response (XDR) capabilities, we are building a next-generation data platform designed for massive scale, real-time intelligence, and high-performance security analytics. --- ## The Role We are looking for a Senior Data Platform Engineer to architect, scale, and optimize the core data infrastructure powering our XDR product. In this role, you will take ownership of the strategic evolution of our data layer — ensuring seamless ingestion, storage, indexing, search, and retrieval of high-volume security telemetry and device data. You will play a key role in transforming our platform into a highly scalable, cost-efficient, secure, and analytics-ready ecosystem that supports real-time detection, investigation, and advanced data science workflows. This is a high-impact individual contributor role focused on architecture, platform modernization, and long-term scalability. --- ## Key Responsibilities - Architect and evolve the data layer to support high-throughput ingestion, real-time processing, and low-latency search across massive datasets. - Evaluate existing search and storage platforms and drive modernization initiatives toward more scalable, performant, and cost-effective solutions. - Design and implement optimized indexing, partitioning, and data structuring strategies for efficient querying and retrieval. - Build and manage scalable data lake architectures that support advanced analytics, threat intelligence, and data science workflows. - Define strategies for lifecycle management, retention, tiered storage, and cost optimization across the data platform. - Ensure high availability, fault tolerance, and disaster recovery across distributed systems. - Implement robust data security controls aligned with XDR and modern cybersecurity frameworks, ensuring data protection at rest and in transit. - Collaborate closely with security engineering, backend teams, and data scientists to bridge raw telemetry ingestion with actionable insights. - Continuously monitor platform performance and lead improvements in reliability, scalability, and operational efficiency. --- ## Qualifications - 6–10 years of professional experience in Data Engineering, Data Platform Engineering, or Distributed Systems Architecture as an Individual Contributor. - Strong hands-on experience with large-scale distributed search and analytics platforms. - Proven experience evaluating and migrating data platforms to improve scalability, performance, and cost efficiency. - Deep understanding of indexing strategies, query optimization, and distributed data storage architectures. - Practical experience designing and operating data lake environments supporting large-scale analytics and machine learning workflows. - Strong knowledge of data lifecycle management, storage tiering, and cost optimization strategies. - Experience implementing security best practices in distributed data systems, especially in security or telemetry-heavy environments. - Solid understanding of high-volume ingestion pipelines and real-time data processing systems. - Bachelor’s degree in Computer Science, Information Technology, or a related technical field. --- ## What We’re Looking For - A systems thinker who can design platforms for scale, not just features. - Someone who can balance performance, cost, and reliability in large distributed systems. - A hands-on architect who can both define strategy and execute technically. - Strong ownership mindset with the ability to independently drive platform-level initiatives. - Experience working in security, cybersecurity, SIEM, or XDR environments is a strong plus.