Job Detail

Benefits

Responsibilities:
 Act as the Engineering Manager for the backend development.
 Creating product roadmaps and quarterly/annual plans along with the product team
 Lead multiple full stack pods and ensuring timely delivery of product features.
 Perform PoCs on new tech areas needed in the platform from time to time.
 Act as the competence manager, building the skills needed in the backend team,
acting as the people manager and developing the growth & development path for
individuals in the team.
 Designing and developing robust and scalable architecture for the product.
 Translating product requirements in engineering designs, code and delivering modules
along with team in defined timelines.
 Iteratively develop next-generation scalable, reliable, flexible, high-performance data
pipeline capabilities and data platforms.
 Be able to connect business and product goals to complex technical tasks.
 Close coordination with DevOps team to define effective and secure deployment
workflows and meet various requirements with best practices.
 Ensure security and robustness of overall tech platform and deployments.
 Coordinating with stack holders like internal management, product team, pre sales and
sales team, clients to ensure the quality and timely delivery of product features and
services.

Requirements:
 Experience of 9+ years in software engineering out of which at least 4 years should have
been spend in designing the systems and managing team of at least 10 people.
 Strong proficiency in system design skills and modelling high scale data intensive
applications from scratch.
 Good hands-on experience in Spring Boot
 Proficient on modelling applications on both RDBMS and NOSQL databases
 Should have experience of developing high scale real time data processing
applications
 Should have experience of defining best practices to followed by team for
coding and system design.
 Should have strong communication and leadership skills
 In-depth knowledge of Apache Kafka, Spark, Flink, Redis, Elastic to develop high scale
applications.
 Good understanding of ML and CV.
 Good team management skills
 Good idea about secure DevOps practices and deployment strategies.

***INTERNAL***

Good to have:
 Exposure to Timeseries Databases, Kubernetes and Docker.
 Exposure to Big Data and data pipeline tools
 Understanding of LLMs and RAG
 Understanding of industry automation and IOT communication protocals.