Engineering Manager(Backend )

Experience Required: 1417 years of overall software engineering experienceCore Focus: Leading teams to build scalable, cloud-native enterprise analytics platforms for global customers. This role blends strong technical leadership, people management, and hands-on system optimization. Core Expectations 1. System Design & Backend Development Drive architectural decisions aligned with data-intensive and API-driven platforms.Own the delivery of complex, multi-service projects with a strict focus on scalability, reliability, and performance.Experience designing and working with microservices, APIs, and event-driven architectures.2. Hands-on Technical Depth & Coding This is a hands-on engineering management role. Candidates must have active, hands-on coding, debugging, and system optimization experience. Core Backend Stack: Strong, current hands-on expertise in Python, Java, or C++.Database Mastery: Excellent SQL skills, including query optimization and handling large datasets within PostgreSQL or SQL-heavy environments.Cloud & Frontend (Plus): Hands-on experience with cloud platforms (GCP is a strong plus) and exposure to frontend technologies like ReactJS.3. Problem Solving & Scaling Proven experience building and managing data-heavy analytics platforms at scale.Deep knowledge of Observability and Application Performance Management (APM), including metrics, logs, and distributed tracing.Establish and mature monitoring, alerting, and root-cause analysis to ensure high availability of production systems.4. Execution & Ownership Lead end-to-end Agile execution, including sprint planning, backlog grooming, retrospectives, and delivery tracking.Partner closely with Product Management and Data Science teams to translate complex business problems into robust engineering solutions.5. Communication Excellent verbal and written communication skills.Ability to clearly present, articulate, and defend technical concepts or trade-offs to business and leadership audiences.6. Leadership Act as a direct coach and mentor to a team of software engineers.Support end-to-end team management, including hiring, onboarding, performance management, and career growth.7. Product & AI Mindset Comfortable working in a fast-paced, customer-centric SaaS product environment.Experience or strong interest in AI-driven technologies, next-generation AI products, and algorithmic forecasting/pricing domain systems is highly preferred. Experience Required: 1417 years of overall software engineering experienceCore Focus: Leading teams to build scalable, cloud-native enterprise analytics platforms for global customers. This role blends strong technical leadership, people management, and hands-on system optimization. Core Expectations 1. System Design & Backend Development Drive architectural decisions aligned with data-intensive and API-driven platforms.Own the delivery of complex, multi-service projects with a strict focus on scalability, reliability, and performance.Experience designing and working with microservices, APIs, and event-driven architectures.2. Hands-on Technical Depth & Coding This is a hands-on engineering management role. Candidates must have active, hands-on coding, debugging, and system optimization experience. Core Backend Stack: Strong, current hands-on expertise in Python, Java, or C++.Database Mastery: Excellent SQL skills, including query optimization and handling large datasets within PostgreSQL or SQL-heavy environments.Cloud & Frontend (Plus): Hands-on experience with cloud platforms (GCP is a strong plus) and exposure to frontend technologies like ReactJS.3. Problem Solving & Scaling Proven experience building and managing data-heavy analytics platforms at scale.Deep knowledge of Observability and Application Performance Management (APM), including metrics, logs, and distributed tracing.Establish and mature monitoring, alerting, and root-cause analysis to ensure high availability of production systems.4. Execution & Ownership Lead end-to-end Agile execution, including sprint planning, backlog grooming, retrospectives, and delivery tracking.Partner closely with Product Management and Data Science teams to translate complex business problems into robust engineering solutions.5. Communication Excellent verbal and written communication skills.Ability to clearly present, articulate, and defend technical concepts or trade-offs to business and leadership audiences.6. Leadership Act as a direct coach and mentor to a team of software engineers.Support end-to-end team management, including hiring, onboarding, performance management, and career growth.7. Product & AI Mindset Comfortable working in a fast-paced, customer-centric SaaS product environment.Experience or strong interest in AI-driven technologies, next-generation AI products, and algorithmic forecasting/pricing domain systems is highly preferred.