Senior DevOps Engineer

Overview

Senior DevOps Engineer on Nexla's data plane team, owning the reliability of a stateful, high-volume streaming platform (Kafka, Spark, Flink, Ray, Redis on EKS and GKE) as an engineering problem.

What you'll do

• Define availability, freshness and latency SLOs that platform and runtime teams agree to, and error budgets that govern release pace.
• Build data-aware instrumentation for consumer lag, throughput, partition skew, job latency and error rates.
• Operate the stateful data plane: Kafka via Strimzi at hundreds of thousands of topics, Spark, Flink and Ray workloads, Redis clusters, and the EKS and GKE clusters underneath, including broker health, checkpointing, backpressure, failover, upgrades and capacity.
• Measure manual operational work and write software to remove it, including Terraform-provisioned infrastructure, runbooks and automation for air-gapped and private enterprise installs.
• Lead root-cause analysis on distributed-systems failures, run blameless postmortems, and drive durable fixes.
• Set the reliability bar other engineers design against and change how teams outside SRE build.

What you'll need

• 8+ years in SRE or infrastructure engineering, most of it operating production distributed data systems rather than application or cloud infrastructure.
• Deep hands-on Kafka at scale in production, ideally on Kubernetes via Strimzi: upgrades, topic and partition management, performance tuning, and TLS and secret rotation.
• Redis and stateful workloads on Kubernetes in production: StatefulSets, PVCs, probes, operators.
• Strong hands-on EKS, including cluster lifecycle and version upgrades.
• Python or similar scripting and programming, and advanced Terraform, with enough range to build tooling other engineers depend on.
• Experience owning SLOs, error budgets or an equivalent reliability contract, and describing a time one changed what a team shipped.
• Use of AI tools in your actual work, with the ability to say specifically where they help and where they mislead.

Nice to have

• Production experience operating Spark, Flink or Ray: resource tuning, checkpointing, failure recovery.
• Operating against Snowflake, BigQuery or similar, including JDBC connectivity and sink reliability.
• Comfort reading and debugging JVM-based systems.
• GKE alongside EKS, Ansible, or broader AWS services such as IAM, VPC, EC2, S3 and Lambda.

Details

• Location: Bengaluru, Karnataka, India; hybrid, 2 days in office.
• Compensation includes base salary and equity.
• Pacific time-zone overlap for leadership meetings and cross-team calls.
• Weekend deployment twice a year.
• Hiring process: 4 conversations over about 2 weeks, including a technical evaluation, technical deep dive, hiring manager round with a short presentation on Express, and a leadership conversation.