Engineering Manager - Data Platform

This role comes under the AppSec Platform charter, focused on designing and developing a multi cloud, portable, OSS backed, streaming first data platform for powering API observability & security products. Additionally the team is also responsible for common services in the authentication & authorization space. The platform serves as the core-pillar for customer facing Analytics & consumption layer for various product modules like Catalog, Run-time Protection, Application/AI Security. You will be expected to manage and grow an engineering team of 8-10 engineers, driving execution, innovation, and delivery of high-impact platform capabilities, drive operational excellence through monitoring, reliability improvements, cost optimization of large-scale data systems and most importantly contribute to the company s mission of becoming a global leader in the AppSec space.

About the Role

• Architect and build large-scale data platforms and microservices-based systems that process and analyze high-volume API traffic.
• Lead project execution from planning to delivery , defining scope, milestones, and deliverables in collaboration with cross-functional teams.
• Ensure engineering teams follow best practices in architecture, coding standards, testing, and security .
• Debug and resolve complex distributed system issues across streaming, storage, and service layers.
• Manage engineering priorities, allocate resources effectively, and ensure timely delivery of projects .
• Drive technical innovation , evaluating and adopting new technologies to improve platform scalability and performance.
• Define and track KPIs for engineering productivity, system performance, and reliability .
• Collaborate closely with product managers, data scientists, and other engineering teams to build features aligned with customer and business needs.

About You

• 9 12 years of overall engineering experience preferably in the platform space.
• At least 2 years of engineering management experience. Proven ability to lead, mentor, and grow teams of 8+ engineers, fostering a high-performance engineering culture.
• Hands-on experience building and scaling distributed data platforms and microservices architectures.
• Strong programming experience in Java, Python, or Go.
• Operational experience with streaming and data processing technologies such as Kafka, Kafka Streams, Flink and Spark.
• Experience with modern analytical and data lake technologies such as Apache Iceberg, Apache Pinot/Druid, ClickHouse etc.
• Familiarity with relational and NoSQL databases.
• Strong understanding of observability, monitoring, and reliability practices for large-scale systems.
• Excellent communication and leadership skills, with experience working across geographically distributed teams.
• Ability to operate effectively in fast-growing startup environments with evolving requirements.