2 days ago
Bengaluru, IndiaSenior
Responsibilities
- Lead delivery, technical direction, architecture reviews, and engineering best practices across platforms and services.
- Design, develop, and operate scalable APIs, distributed systems, microservices, and data platforms.
- Build and manage data lakehouse ingestion, transformation, orchestration, governance, warehousing, and analytics capabilities.
- Drive observability, monitoring, root-cause analysis, production support, incident management, reliability engineering, and service health management.
- Define and manage SLOs, SLAs, operational runbooks, troubleshooting guides, capacity planning, and disaster recovery processes.
- Implement CI/CD, automated testing, release automation, deployment practices, cloud-native development, containerization, and infrastructure automation.
- Mentor, hire, and coach engineers while fostering technical excellence and collaboration with Product, Design, and Program Management.
- Adopt AI-assisted practices for development, testing, code review, documentation, observability, incident triage, automation, and developer productivity.
Requirements
- Extensive experience designing, developing, and operating scalable applications with Go and Python, including REST and/or GraphQL APIs.
- Strong expertise in distributed systems, microservices, system design, scalability, reliability, and performance optimization.
- Deep knowledge of PostgreSQL, Redis, ClickHouse, or equivalent OLTP, caching, and analytics technologies.
- Experience with data modeling, query optimization, indexing, caching strategies, analytics architectures, data engineering, and large-scale data processing.
- Hands-on Data Lakehouse experience covering ingestion, transformation, orchestration, governance, warehousing, and analytics.
- Experience with ELK Stack and Grafana for logging, metrics, tracing, dashboards, and alerting.
- Experience with software quality practices including unit testing, integration testing, code reviews, static analysis, and technical debt management.
- Experience integrating security into the SDLC and applying secure development, compliance, auditability, and data governance practices.
- Strong understanding of cloud-native development, containerization, orchestration, infrastructure automation, Infrastructure as Code, high availability, fault tolerance, and cost efficiency.
- Experience defining operational processes, handling incidents, and managing service reliability and capacity.
- Demonstrated engineering leadership through architecture reviews, technical decision-making, mentoring, hiring, and coaching.
- Experience adopting AI-first engineering practices and knowledge of responsible AI governance, security, compliance, and quality controls.
- Exposure to agentic AI, LLM orchestration, prompt engineering, tool-calling workflows, AI-assisted automation, RAG architectures, vector search, knowledge retrieval, and AI-powered applications is preferred or desirable.
- Background in streaming platforms, event-driven architectures, large-scale analytics systems, and regulated environments is a plus.
- Typically requires at least 8 years of related experience and a bachelor's degree or higher in Computer Science, Engineering, Information Technology, or a related technical discipline.
Tech Stack
Categories
BackendData Engineering
About NetApp
NetApp builds data storage and data management software and hardware for enterprises, including ONTAP-powered all-flash arrays and hybrid cloud services that integrate with AWS, Azure, and Google Cloud. It sells systems and subscriptions that support backup, disaster recovery, databases, and container/Kubernetes workloads. Founded in 1992 and headquartered in San Jose, California, NetApp is a public company listed on NASDAQ.