Java Team Lead

Job Description: You will be joining LeanQubit, a Certified Integrator of Ignition, dedicated to crafting custom Ignition-based solutions for manufacturing, energy, and utility industries. Based in Mumbai, LeanQubit invites potential partners to connect with them. Role Overview: As a Java Team Lead for a hybrid/remote role in Mumbai, you will lead a team of developers, oversee Java-based applications" design and implementation, and ensure best practices are followed. Your responsibilities will include managing microservices architecture, applying design patterns, and driving the software development lifecycle. Key Responsibilities: - Lead the design, development, and deployment of complex software systems. - Architect scalable, low-latency systems for high-volume, high-frequency data processing. - Optimize Java applications for performance, memory usage, and concurrency. - Design and manage efficient, scalable database architectures. - Integrate machine learning models into production systems and pipelines. - Collaborate with cross-functional teams including data scientists, DevOps, and product managers. - Conduct code reviews, mentor team members, and enforce engineering best practices. - Stay current with emerging technologies and recommend adoption where appropriate. Technical Skills Required: 1. Programming & System Design: - Expertise in Java, including Collections framework, concurrency, multithreading, and JVM internals. - Efficient memory management, garbage collection tuning, and profiling. - Designing for low-latency, high-throughput, and real-time processing. - Strong grasp of data structures and algorithms. - Experience with distributed systems, microservices, and event-driven architectures. 2. Database Engineering: - Advanced experience with relational databases like PostgreSQL, MySQL, Oracle. - Familiarity with NoSQL databases such as MongoDB, Cassandra, Redis. - Skills in query optimization, indexing, partitioning, sharding, and replication. - Data modeling for both OLTP and OLAP systems. - Experience with streaming data and time-series databases. 3. AI & ML: - Working experience with data scientists for ML model integration. - Familiarity with ML frameworks like TensorFlow, PyTorch, Scikit-learn. - Understanding of model serving and experience with feature engineering and data pipelines. 4. Cloud & DevOps: - Hands-on experience with AWS, Azure, or GCP. - Proficiency in CI/CD pipelines, containerization, and Infrastructure as Code. 5. Testing & Quality: - Skills in unit and integration testing, performance testing, and using code quality tools. 6. Collaboration & Agile: - Proficiency in Git-based version control, Agile/Scrum methodologies, and tools like JIRA, Confluence, Slack. Preferred Qualifications: - Experience in real-time analytics, MES, or IoT platforms. - Certifications in Java, cloud platforms, or AI/ML. - Strong communication, leadership, and mentoring skills.,