Engineering Manager - Data Platform

Split Software; Bengaluru; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

Split Software in Bengaluru is seeking an experienced engineering manager to lead a team focused on designing and developing a multi-cloud, portable data platform for API observability and security. The role involves managing engineering priorities, fostering best practices, and driving technical innovation.

Ideal candidates will have 9–12 years of engineering experience, including hands-on experience with distributed data platforms and strong leadership skills. Experience with technologies like Kafka, Java, and Python is essential.

Qualifications

• 9–12 years of overall engineering experience preferably in the platform space.
• At least 2 years of engineering management experience leading teams of 8+ engineers.
• Hands-on experience with distributed data platforms and microservices architectures.
• Strong programming experience in Java, Python, or Go.
• Operational experience with streaming technologies such as Kafka.
• Familiarity with relational and NoSQL databases.

Responsibilities

• Architect and build large-scale data platforms and microservices-based systems.
• Lead project execution from planning to delivery.
• Ensure engineering teams follow best practices in architecture and security.
• Debug and resolve complex distributed system issues.
• Define and track KPIs for engineering productivity and system performance.

Skills

Engineering Management

Distributed Data Platforms

Microservices Architecture

Java

Python

Go

Kafka

Flink

Spark

Observability

Tools

Apache Iceberg

Apache Pinot

Druid

ClickHouse

Job description

Position Summary

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 responsible for common services in the authentication & authorization space. The platform serves as the core pillar for the customer-facing analytics & consumption layer for various product modules such as 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, driving operational excellence through monitoring, reliability improvements, cost optimization of large‑scale data systems, and most importantly contributing 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.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex or national origin.