Up Full stack java Jobs – 98 Open Jobs Today

Performance Test Architect- Noida, India
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- Full-time
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IN_Senior Associate_Data Analyst _D&A_Advisory_Noida
PwC —Noida, Uttar Pradesh
- Full-time
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CredAble —Noida, Uttar Pradesh
- Full-time
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Friends Color Images —Noida, Uttar Pradesh
- Full-time
- Azure
- Java
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- Commuter assistance
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Team Leader - Technology Services
MetLife —Noida, Uttar Pradesh
- Full-time
- Java
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7d
IN_Senior Associate_Data Science_D&A_Advisory_Noida
PwC —Noida, Uttar Pradesh
- Full-time
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- Engineering
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Amrut Software —Noida, Uttar Pradesh
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EY —Noida, Uttar Pradesh
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RxLogix —Noida, Uttar Pradesh
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Sr. Developer - Application Development Microsoft P 4B
Genpact India Pvt. Ltd. —Noida, Uttar Pradesh
- Full-time
- Hybrid work
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Performance Test Architect- Noida, India

NeoXam -
Noida, Uttar Pradesh

Apply Now

Job details

Qualifications

CI/CD
ISTQB Certification
Elasticsearch
Azure
Oracle
Go
Kubernetes
Ansible
Microsoft SQL Server
Git
Performance testing
Java
SQL
AWS
Docker
PostgreSQL
Terraform
Continuous integration
RabbitMQ
REST
Mentoring
Scripting
GitHub
APIs
Kafka
gRPC
Leadership
Jenkins
GitLab
Python

Full job description

Our Context

At NeoXam, we are looking for a Performance Test Architect to build and lead our performance engineering practice from the ground up. You will own the end-to-end performance strategy for the ARO platform — from designing the test lab infrastructure and crafting benchmarking frameworks to embedding performance validation into our CI/CD pipelines. This is a high-impact, hands-on leadership role where you will shape how we measure, optimize, and guarantee the performance of a complex distributed system under real-world capital markets workloads.

Required Qualifications

10+ years of hands-on experience in performance testing and engineering for large-scale, distributed enterprise applications
Deep expertise with load testing tools: JMeter, Gatling, and/or k6 — including scripting complex scenarios, correlation, parameterization, and custom plugins
Strong experience with Kubernetes and Docker: understanding of pod scheduling, resource limits, HPA/VPA, and their impact on application performance
Proven track record of building performance test frameworks integrated into CI/CD pipelines (Jenkins, GitLab CI, or GitHub Actions)
Hands-on experience with monitoring and observability stacks: Grafana, Prometheus, ELK (Elasticsearch, Logstash, Kibana), or similar APM tools
Solid understanding of database performance: SQL tuning, indexing strategies, connection pooling, and behavior under concurrent load (PostgreSQL, Oracle, or SQL Server preferred)
Experience with message queue systems (RabbitMQ, Kafka, or ActiveMQ) and API performance testing (REST/gRPC)
Proficiency in at least one programming language (Java, Python, or Go) for scripting, tooling, and automation
Experience leading or mentoring a team of 2+ engineers in performance testing or related disciplines

Preferred Qualifications

Domain experience in capital markets, financial services back-office operations, or reconciliation systems
Experience performance testing shared-database architectures with multiple concurrent services
Familiarity with Infrastructure-as-Code (Terraform, Ansible) and GitOps practices
Experience with chaos engineering tools (Litmus, Chaos Monkey) for resilience testing
Certifications in performance engineering (e.g., ISTQB Performance Testing, AWS/GCP/Azure certifications)
Experience with financial data volumes: millions of positions/trades per reconciliation cycle

Key Responsibilities

Performance Test Lab & Infrastructure

Design, build, and maintain a dedicated performance test lab that mirrors production Kubernetes environments (namespaces, resource quotas, network policies, storage classes)
Provision and manage test infrastructure using Infrastructure-as-Code (Terraform, Helm charts) for repeatable, version-controlled environments
Set up isolated test databases with realistic data volumes (millions of reconciliation records) and configure MQ/API test harnesses for inter-module communication
Establish baseline hardware and configuration profiles for consistent benchmarking across releases

Test Strategy & Benchmarking

Define the comprehensive performance test strategy covering load, stress, soak, spike, capacity, and scalability testing across all modules
Create workload models based on real production traffic patterns — peak reconciliation windows, batch processing cycles, concurrent user simulations, and MQ throughput scenarios
Establish KPIs and SLAs: response time percentiles (P50/P95/P99), throughput (TPS), resource utilization ceilings (CPU, memory, IOPS), reconciliation processing rates, and error thresholds
Design module-level and end-to-end integration performance test suites that validate the shared database model under concurrent multi-module access
Build automated benchmarking frameworks that produce comparable, versioned performance reports across releases

CI/CD Integration & Shift-Left Performance

Embed performance test gates into Jenkins/GitLab CI/GitHub Actions pipelines so that every build is validated against performance baselines before promotion
Implement automated regression detection: flag builds that degrade response times or throughput beyond configurable thresholds
Create lightweight smoke performance tests for PR-level validation and full-scale suite execution for nightly/release pipelines
Integrate with Grafana/Prometheus/ELK for real-time test execution dashboards, trend analysis, and alerting on performance anomalies

Analysis, Optimization & Collaboration

Perform deep-dive root cause analysis of performance bottlenecks using profiling tools, APM traces, thread dumps, and database execution plans
Partner with development teams to recommend and validate optimization strategies (query tuning, caching, connection pooling, async processing, horizontal scaling)
Produce executive-level performance reports with clear findings, risk assessments, and capacity projections for product leadership
Evaluate and benchmark database performance under the shared-DB model, including connection contention, lock analysis, and read/write throughput under concurrent module load

Team Leadership

Recruit, mentor, and lead a team of 2–4 performance engineers, establishing best practices, coding standards, and review processes
Drive a culture of performance awareness across engineering — conduct training sessions, brown-bags, and create internal knowledge base documentation
Define career growth paths and skill development plans for the performance engineering team

Apply Now

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full stack java jobs in up

Performance Test Architect- Noida, India

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Senior AI/ ML Engineer

Team Leader - Technology Services

IN_Senior Associate_Data Science_D&A_Advisory_Noida

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SAP BASIS-Senior

Technical Architect

Sr. Developer - Application Development Microsoft P 4B

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