Java Technical Lead

Job Title: Java Technical Lead

Experience Required: 10-15 Years

Assignment Duration: NA

Engagement Type: Fulltime

Work Location: Bloomfield, CT

Key Responsibilities: Architect and lead the development of highly available Java microservices

deployed on Google Cloud Platform

Own end-to-end system design, including API contracts, data consistency,

scalability, and fault tolerance

Design and implement event-driven architectures using Pub/Sub and Kafka-

based messaging platforms

Write, review, and optimize Java 8 / Java 11 code with strong focus on

concurrency, performance, and correctness

Drive JVM tuning and performance optimization, including analysis and

memory profiling in production

Lead containerized deployments using Docker and Google Kubernetes Engine

(GKE)

Define and enforce distributed system guarantees, such as idempotency, retry

strategies, ordering, and back-pressure handling

Design and manage CI/CD pipelines supporting zero-downtime deployments

(blue-green, canary)

Collaborate with DevOps, Security, SRE, and Product teams to evolve platform

architecture

Lead incident response, root cause analysis (RCA), and long-term remediation

initiatives

Ensure systems meet security, compliance, and reliability standards, especially

in regulated environments

Mentor senior engineers and serve as the technical escalation and decision

authority

This role is for engineers who:

Still write complex Java code

Own architecture and failure modes

Have lived through production outages

Understand performance, scalability, security, and cost trade-offs

This is not a people-only or documentation-only lead role.

Required Technical

Expertise:

The candidate must have 10-15 years of hands-on experience in Java, with

strong expertise in Java 8 and Java 11, including streams, concurrency, and the

Java Memory Model.

Strong experience is required in J2EE fundamentals, along with extensive

hands-on development using Spring Boot, Spring MVC, and Spring Security.

The candidate must have designed and implemented microservices

architectures, applying enterprise and distributed system design patterns in

real production environments.

Proven experience with Hibernate ORM and JPA is required, including

performance tuning and transactional behavior.

The candidate must have hands-on experience designing and deploying

applications on Google Cloud Platform (Google Cloud Platform), including Compute Engine, Cloud

Storage, and Cloud Load Balancing.

Strong experience with Google Kubernetes Engine (GKE) is required, including

container orchestration, scaling, and deployment strategies.

The candidate must have worked with Pub/Sub for asynchronous messaging

and event-driven architectures.

Deep experience with JVM internals, including tuning, heap dump analysis,

and memory leak resolution

Strong understanding of distributed systems theory, including CAP theorem,

eventual consistency, and trade-offs

Experience with resilience patterns, such as circuit breakers, bulkheads, retries,

and graceful degradation

Hands-on experience with API security, including OAuth2, JWT, and Zero Trust

principles

Experience implementing distributed tracing and observability using

OpenTelemetry, ELK, Prometheus, or Grafana

Experience working in regulated domains such as banking, payments,

healthcare, or insurance

Ability to design cost-efficient cloud architectures while maintaining

performance and reliability

Experience using Cloud Functions and API Gateway / Apigee for building

scalable APIs is required.

The candidate must have strong experience with Kafka, including partitioning

strategies, consumer groups, rebalancing behavior, and failure handling.

Hands-on experience with ActiveMQ or RabbitMQ is required for message-

based integration.

The candidate must have worked with NoSQL database (Bigtable) in distributed

environments.

Strong understanding of Redis caching, including eviction strategies and

consistency challenges, is required.

The candidate must have hands-on experience building and maintaining CI/CD

pipelines using Jenkins.

Experience with configuration management and automation tools - Ansible,

Chef, and Puppet, is required.

Strong understanding of containerized application lifecycle management using

Docker is required.

The candidate must have experience implementing monitoring, logging, and

alerting for distributed systems.

Proven ability to perform production troubleshooting, performance analysis,