Senior DevOps Engineer

Location: Bangalore

Experience: 8-10+ years

Type: Full-time

Role Overview

We are seeking a highly skilled Senior DevOps Engineer to lead infrastructure and deployment efforts for our next-generation data and AI platform. This role focuses on building resilient, scalable systems for on-premises and hybrid environments, supporting microservices, real-time data streaming, and batch processing.

You will work closely with architects and engineering teams to design, automate, and scale infrastructure for mission-critical applications involving Kafka, Spark, and distributed storage systems.

Key Responsibilities

Infrastructure Design & Automation

• Architect and maintain hybrid and on-premises environments for compute and storage workloads.
• Deploy and manage containerized microservices using Kubernetes (on-prem and cloud).
• Automate infrastructure provisioning using Terraform, Ansible, or similar tools.
• Configure and scale distributed data streaming and storage platforms (eg: Kafka clusters, Apache Spark, and data lake/warehouse).

Scalability & Performance

• Design for elastic scaling, load balancing, and resource isolation for data services and APIs.

Security & Governance

• Secure hybrid deployments with VPNs, firewalls, and identity management.
• Implement data access controls, audit trails, and encryption across services and storage layers.
• Manage secrets securely across environments.

Monitoring, Logging & Resilience

• Set up observability stacks (Prometheus, Grafana, ELK, OpenTelemetry) for real-time insight.

CI/CD & Operations

• Build pipelines to deploy services, data jobs, and configuration changes to hybrid infra.
• Maintain and enhance CI/CD pipelines for zero-downtime deployments and rollbacks.
• Support SRE practices including incident management, post-mortems, and runbook creation.

Required Skills

• Bachelor’s or Master’s in Computer Science, Engineering, or related field.
• 8+ years in DevOps and SRE roles.
• Strong experience with hybrid and on-premKubernetes deployments.
• Proficiency in infrastructure automation (Terraform, Ansible, Helm).
• Experience with data processing and microservices orchestration, supporting real-time data platforms in hybrid or on-premises environments.
• Solid understanding of networking, storage, firewalls, and security for hybrid deployments.
• Programming/scripting experience with Bash, Python, or Go.
• Strong grasp of DevOps best practices, observability, and system reliability engineering.

Good to Have

• Experience with data lake/warehouse platforms (HDFS, S3-compatible storage, Redshift, Snowflake).
• Knowledge of event-driven architectures, ETL/ELT pipelines, and data mesh concepts.
• Exposure to machine learning operations (MLOps) or data science workflows.

• Certifications in Kubernetes, cloud platforms, or security are a plus.