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Cognite

Industrial data platform with AI

Senior Database Reliability Engineer

Database AdministrationConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 6 years of experience in Database Reliability Engineering, Database Engineering, Site Reliability Engineering, Platform Engineering, or a closely related role.
  • Strong hands-on experience operating PostgreSQL at scale, preferably in cloud-managed environments.
  • Strong experience with Elasticsearch, including cluster administration, performance tuning, scaling, shard management, and troubleshooting.
  • Experience operating databases and stateful workloads on Kubernetes.
  • Experience with Kafka or another distributed database or storage system.
  • Strong Infrastructure as Code experience with Terraform or similar tools.
  • Experience with at least one major cloud platform: Azure, AWS, or Google Cloud Platform, with preferred exposure to multi-cloud environments.
  • Strong understanding of database reliability principles, including high availability, disaster recovery, backups, replication, capacity planning, and observability.
  • Proficiency in scripting or programming using Python, Go, or a similar language.
  • Experience automating repetitive operational tasks and building self-service infrastructure.
  • Strong troubleshooting and incident-management skills, with the ability to diagnose complex distributed-system failures.

Responsibilities

  • Standardize and automate lifecycle management for a fleet of more than 1,000 PostgreSQL instances across Azure, AWS, and Google Cloud Platform.
  • Build and maintain infrastructure using Infrastructure as Code and automation frameworks.
  • Automate provisioning, configuration, patching, upgrades, backups, and operational workflows.
  • Improve consistency and reliability across the PostgreSQL fleet while reducing manual operational effort.
  • Work with Azure Database for PostgreSQL Flexible Server, Amazon RDS, and Google Cloud SQL.
  • Evolve provisioning and configuration using Kubernetes-based and Terraform-driven workflows.
  • Design, operate, and scale high-performance Elasticsearch clusters across Elastic Cloud and self-managed Kubernetes environments using ECK.
  • Own the reliability and performance of Elasticsearch infrastructure supporting search, semantic retrieval, vector workloads, and high-volume operational data.
  • Establish best practices for cluster sizing, capacity planning, shard management, upgrades, backups, monitoring, and disaster recovery.
  • Support Elasticsearch deployments where PostgreSQL is the source of truth and environments where Elasticsearch is the authoritative datastore.
  • Build automation to simplify provisioning and lifecycle management across Elastic Cloud and ECK.
  • Improve security, connectivity, zone awareness, and operational resilience across multi-cloud deployments.
  • Own the reliability, scalability, and performance of Kafka clusters supporting high-throughput, low-latency event streaming.
  • Operate Kafka in self-managed Kubernetes-based configurations, including Strimzi and Kafka Operator, and managed configurations such as Confluent Cloud and Amazon MSK.
  • Drive capacity planning, partition and topic design, replication strategy, and broker-level performance tuning.
  • Establish and automate best practices for upgrades, rolling restarts, backups, disaster recovery, and schema evolution using tools such as Schema Registry.
  • Build monitoring and alerting for consumer lag, broker health, in-sync replica status, and throughput to enable early incident detection.
  • Partner with Software Engineering to ensure producer and consumer patterns, retention policies, and topic ownership scale as usage grows.
  • Automate database provisioning and lifecycle operations so they become repeatable.
  • Reduce operational toil across PostgreSQL, Elasticsearch, and Kafka.
  • Enable database platforms to scale reliably with business and customer growth.
  • Detect incidents early and resolve them through automation and observability.
  • Maintain consistent and resilient database infrastructure across Azure, AWS, Google Cloud Platform, and private-cloud environments.
  • Enable engineering teams to consume reliable database infrastructure without significant manual Database Reliability Engineering intervention.

Desired Qualifications

  • Experience with Kafka and fdb-kubernetes-operator.
  • Experience with Elastic Cloud and ECK.
  • Proficiency in Go for building automation, tooling, or operators; Python or another scripting language is a plus.
  • Experience managing PostgreSQL through Kubernetes operators or custom resources.
  • Experience with Kubernetes operators and building automation for stateful workloads.
  • Experience operating databases across multi-cloud and private-cloud environments.
  • Experience with observability platforms and database performance monitoring.
  • Familiarity with distributed systems, data replication, consistency, and failure-domain design.

About the Company

Cognite

Industrial data platform with AI

Cognite provides cloud-based data and AI platforms for industrial companies to digitize and optimize operations. Its flagship Cognite Data Fusion connects OT, IT, and engineering data, unifying sensor data, maintenance logs, and 3D models into a real-time view of assets to improve performance and safety. Cognite Atlas AI is a low-code platform that lets engineers build AI agents for predictive maintenance, anomaly detection, and production optimization without deep coding. The company differentiates itself through deep cross-domain data integration for asset-heavy industries and a scalable cloud environment to accelerate industrial digitalization and deliver measurable value.

Company size
501-1,000
Company stage
Acquired
Total funding
$225.3M
Headquarters
Tempe, AZ
Founded
2016

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