Database Reliability Engineer

Concentrix; India; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Concentrix seeks a Developer with Database Reliability Engineer skills focusing on Node.js, TypeScript, and cloud databases. You will own tooling around MongoDB Atlas and Elasticsearch/OpenSearch, while ensuring production reliability and data movement between multiple databases.

Deep production experience with MongoDB Atlas, Elasticsearch/OpenSearch, and Firestore is valued, along with Terraform and Jenkins for infra as code. Remote-first environment with international collaboration.

Qualifications

• 3+ years with Node.js and TypeScript, able to debug unfamiliar code and build production services.
• 3+ years of hands-on production MongoDB Atlas experience with index design and explain analysis.
• 2+ years operating Elasticsearch/OpenSearch in production with cluster health and performance focus.
• Working knowledge of Redis or Valkey, including memory and eviction concepts.
• Working knowledge of Firestore or equivalent document store.
• Experience with large production datasets and cross-service data movement.
• Terraform and Jenkins for infrastructure as code and CI/CD.
• Google Cloud and/or AWS fundamentals for cloud deployments.

Responsibilities

• Build and maintain Node.js/TypeScript services and workers for database tooling.
• Debug database usage inside other teams' codebases and provide precise diagnostics.
• Develop self-service tooling for index usage, audits, dashboards, and cost metrics.
• Contribute to AI-assisted database tooling and performance best practices.
• Administer MongoDB Atlas clusters and OpenSearch/Elasticsearch clusters with high availability.
• Participate in on-call rotations and incident response with runbooks and RCAs.
• Advise engineering on database selection and design decisions.

Skills

Node.js

TypeScript

MongoDB Atlas

Elasticsearch/OpenSearch

Redis/Valkey

Firestore

Google Cloud

AWS

Terraform

Jenkins

Kubernetes

Tools

Terraform

Jenkins

Kubernetes

Google Cloud

AWS

Job description

We’re Concentrix. A new breed of tech company — Human-centered. Tech-powered. Intelligence-fueled.

We create game-changing solutions across the enterprise, that help brands grow across the world and into the future. We are trusted by clients across all major sectors, from up-and-coming success stories to iconic Fortune Global 500 brands in over 70 countries spanning 6 continents.

* Challenge Conventions

* Create experiences that go beyond WOW

If this is you, we would love to discuss career opportunities with you.

In our Information Technology and Global Security team, you will deliver the latest technology infrastructure, transformative software solutions and industry-leading global security for our staff and clients. You will work with the best in the world to design, implement and strategize IT, security, application development, innovation, and solutions in today’s hyperconnected world. You will be part of the technology team that is core to our vision of develop, build and run the future of CX.

Concentrix provides eligible employees with an opportunity to enroll in many benefit programs, generally including private medical plans, great compensation package, retirement savings plans, paid learning days, and flexible workplaces. Specific benefits plans will vary by country/region.

• We’re a remote-first company looking for the absolute best talent in the world. Experience the power of a game-changing career.

Position Overview:

Job Title: Developer with Database Reliability Engineer (NodeJS+MongoDB Atlas+Elastic Search) Skills

Overall profile: A developer with strong cloud database experience — someone who is comfortable writing and debugging Node.js and TypeScript, and who has also carried real production ownership of managed cloud databases. The two anchor skills are MongoDB Atlas and Elasticsearch/OpenSearch, with working knowledge of Redis or Valkey.

Platform Data owns the databases and data pipelines behind every Client product line: MongoDB Atlas, Elasticsearch and OpenSearch, ClickHouse, Redis and Valkey, and Firestore, running 24x7 on Google Cloud and AWS and provisioned as code with Terraform and Jenkins. Product teams build features; we keep the data layer underneath them fast, cost-efficient and available.

Depth we expect by engine

MongoDB Atlas - Deep — you have owned this in production

Elasticsearch / OpenSearch - Deep — you have operated clusters, not just queried them

Redis / Valkey

Working knowledge — memory, eviction, key design

Firestore - Working knowledge, or a close equivalent document store

ClickHouse - Not expected. This is the one engine we are happy to teach you.

Responsibilities:

Primary focus — build and debug the tooling

• Build and maintain Node.js and TypeScript services and workers that operate our databases: the Platform Data control-plane API (MongoDB index and migration APIs, Elasticsearch template management, ClickHouse cluster bootstrap) and the change-data-capture workers that move data between MongoDB, Firestore, ClickHouse and Elasticsearch.
• Debug database usage inside other teams’ codebases — read an unfamiliar service, find the query or connection-pool problem behind an alert, and either fix it or give the owning team a precise diagnosis.
• Build automation and self-service tooling so teams can help themselves: index usage reporting, query shape audits, cost and storage dashboards, capacity sizing tools.
• Contribute to our internal AI-assisted database tooling — a Query AI assistant with Atlas cost and index intelligence, a ClickHouse workload advisor, and a library of machine-readable database best practices.

Secondary focus — operate the fleet

• Administer MongoDB Atlas: index strategy, shard keys, connection-pool sizing, replica-set behaviour, explain analysis, cluster-to-cluster migrations, backup and restore.
• Operate Elasticsearch and OpenSearch clusters — our largest single source of on-call load. Cluster health and yellow or red recovery, shard sizing, templates and mappings, storage and lifecycle policies, snapshot and restore, reindexing, and tracing data-node CPU or slow queries back to the query shape that caused them.
• Keep Redis and Valkey healthy: memory growth and big keys, TTL and eviction policy, cluster versus instance mode.
• Provision and change database infrastructure through Terraform and Jenkins across all five engines, and review database infrastructure pull requests.
• Participate in the on-call rotation: triage alerts from Grafana through logs and traces to code, act from runbooks, escalated with context, and write the root cause analysis afterwards.
• Own capacity planning and cost efficiency across the fleet, and keep runbooks current. Pick up ClickHouse partitioning and materialized-view work as you ramp.

Across both — advising the engineering org

• Decide which database fits a use case, and defend the choice. Teams consult us before they build: Firestore or Atlas, a new search index or a better query, denormalise or join, cache or read replica. You own these recommendations, including the scale and cost thresholds at which the answer changes.
• Review schemas, indexes and query patterns before they reach production, and turn recurring findings into standards and sizing guides rather than repeated one-off advice.
• Help developers understand the databases they use. Our long-term leverage comes from teams deciding well without us in the room, so explaining why a query behaves as it does matters as much as fixing it.

Skills required

• 3+ years with Node.js and TypeScript, strong enough to debug an unfamiliar codebase and build a production service or worker, not only scripts.
• 3+ years of hands‑on production MongoDB, specifically MongoDB Atlas — index design, shard keys, explain analysis, connection pools, and accountability when a cluster degrades.
• 2+ years operating Elasticsearch or OpenSearch in production — shard strategy, mappings and index templates, cluster health and recovery, storage management, and query performance troubleshooting. Managed offerings (AWS OpenSearch Service, Elastic Cloud) are what we run.
• Working knowledge of Redis or Valkey: memory behaviour, eviction and TTL policy, key design, instance versus cluster mode. You need not have run large fleets, but you should be able to explain why one is running out of memory.
• Working knowledge of Firestore, or a close equivalent managed document store.
• Experience with large production datasets — multi-terabyte collections and indices, billions of documents. What is safe at 10 GB is not safe at 10 TB, and we need someone who already knows where those lines fall.
• Database selection and design judgement. You can recommend the right store for a new use case and give reasons — access patterns, write volume, consistency, and the thresholds at which your answer would change — then explain it to a product engineer who does not share your background.
• Monitoring depth: Grafana and Prometheus, building dashboards rather than only receiving alerts, plus engine-native tooling — Atlas monitoring, Performance Advisor and Query Profiler, and OpenSearch cluster and slow-query monitoring.
• Google Cloud (or equivalent) fundamentals: IAM, VPC and private connectivity, secret management, Pub/Sub, Kubernetes.
• Terraform, plus enough Kubernetes and Helm to read a chart and change a worker deployment safely.
• A real on‑call rotation, with established change and incident management practices.
• Excellent written and verbal communication. RCAs, runbooks, design notes and guidance to other teams are how this team creates leverage.

Good to have

• ClickHouse, or another columnar analytics store — genuinely optional; this is the engine we expect to teach
• Firestore to MongoDB migration experience
• Change-data-capture and streaming pipelines — change streams, Pub/Sub or Kafka, backpressure and delivery-guarantee concerns
• Schema-as-code tooling such as Liquibase for index and mapping migrations
• Python, Go or Bash as a secondary language
• Experience building AI or LLM-assisted internal tooling, or MCP servers
• Demonstrable database cost optimization work