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Sr. Software Engineer : Mastercard

Shiftcode Analytics, Inc

O Fallon, MO

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JOB DETAILS
SALARY
$60–$65 Per Hour
SKILLS
Amazon Web Services (AWS), Analysis Skills, Apache ActiveMQ, Apache Kafka, Application Programming Interface (API), Autoscaling, Booting, Budgeting, CPU (Central Processing Unit), Caching, Cloud Computing, Concurrency, Continuous Deployment/Delivery, Continuous Integration, Cryptography, DNS (Domain Name System), Debugging Skills, Distributed Computing, Docker, F5 Network Software, File Systems, Financial Systems, Hybrid Cloud, Input/Output, JUnit, Java, Jenkins, Linux Operating System, Load Balancing, Memory Hardware, Microservices, Middleware, Network Performance/Analysis, Payment Processing, Performance Analysis, Performance Modeling, Private Cloud, Production Systems, Productivity Model, Quality Assurance Methodology, REST (Representational State Transfer), RabbitMQ, Radiography, Redis, Replication and Remote Mirroring, Root Cause Analysis, SSL-TLS (Secure Socket Layer - Transport Layer Security), Software Engineering, Software as a Service (SaaS), System Architecture, Virtualization, nginx Web Server
LOCATION
O Fallon, MO
POSTED
3 days ago
Interview : Video + F2F

Visa : USC, GC

This is hybrid from day-1

Role 1 )

Sr. Java Developer
Rate : 50-55
  • Extensive knowledge and experience with Java, Spring Boot, gRPC
  • Good knowledge in creation and working with CI/CD pipelines using Jenkins
  • Experienced in event driven systems (ActiveMQ, Apache Kafka, NATS, etc)
  • Experience in financial system encryption (PIN Blocks, CHIP, CVC) would be beneficial
  • Experience with testing frameworks and methodologies (Gtest, JUnit, BlazeMeter, mocking, etc.)
  • Experienced in building platforms with Microservice architecture and RESTful APIs.
  • Experience using cloud-native approaches running on Linux, leveraging Spring Boot
  • Exposure to symmetric cryptography would be desired.
  • Experience with virtualization like Cloud Foundry (PCF), Kubernetes (EKS), Docker etc.

Role 2 )

Lead Java Developer

Rate : $60-65 ( buying )

Responsible for identifying and resolving end-to-end performance bottlenecks across distributed systems, Spring Boot services, middleware components, and hybrid cloud environments (private cloud + AWS). This role goes far beyond traditional testing by deeply analyzing container orchestration, networking paths, and system interactions under load. This position maps full system workflows, sets realistic latency budgets, and ensures each component meets its SLOs. Ideal candidates have extensive experience with high-scale, multi-region, and high-transaction platforms (e.g., financial systems, payment processing, or large enterprise SaaS) running in a Cloud environment.

Key Responsibilities
  • Define service-level objectives (SLOs), performance budgets, and latency/throughput targets across services.
  • Architect and champion comprehensive distributed tracing strategies (Dynatrace, AWS X-Ray, etc.).
  • Analyze application, platform, and cloud behavior using deep-dive techniques such as heap dumps, thread dumps, flame graphs, GC logs, network traces, and storage I/O profiling.
  • Review service and system architectures for performance risks (e.g., synchronous hops, excessive dependencies, misconfigured connection pools, poor cache placement).
  • Conduct and lead root-cause analysis for performance incidents in production and pre-production environments.
  • Develop capacity models and performance baselines for services running across cloud environments.

Areas of Expertise
  • Application Layer: Spring Boot internals, JVM tuning, thread/heap management, concurrency debugging, GC optimization
  • Container Runtime: PCF, Docker, container resource limits, CPU throttling, memory pressure
  • Orchestrators: PCF, Kubernetes, ECS (autoscaling, pod health, scheduling issues)
  • Networking: Service-to-service hops, TLS overhead, DNS, routing, load balancer configs (F5, Nginx, ALB/NLB), service mesh performance
  • Storage: Latency, IOPS constraints, distributed file system behavior
  • Caching & Middleware: Redis, Hazelcast, NATS, Kafka, RabbitMQ configuration and throughput tuning
  • Databases: Connection pool tuning, slow queries, indexing, replication lag
  • Cloud Layer: AWS compute/storage/network performance, regional latency, cross-cloud traffic patterns

About the Company

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Shiftcode Analytics, Inc