DevOps Consultant

Title: Senior DevOps Engineer – On-Premise & Hybrid Cloud 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-prem Kubernetes 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.