We are seeking a highly skilled Lead Full Stack Engineer to join a high-impact engineering team building a next-generation Operational Data Hub . This platform acts as a central “book of record” for enterprise data , enabling seamless data ingestion, processing, and distribution to downstream systems through real-time streaming and API-driven architecture . The team is driving a critical transformation from batch-based processing to real-time data streaming , supporting scalable and event-driven financial systems. As a Lead Engineer, you will play a key role in designing, developing, and modernizing distributed systems , while remaining hands‑on and contributing directly to code. What You’ll Do Full Stack Development Design, build, and maintain scalable applications across the full stack Develop robust backend services and APIs using Java and Spring Boot Contribute to frontend and integration layers as needed Real-Time Data & Streaming Build and enhance real-time data pipelines and ingestion frameworks Work with streaming platforms such as Kafka, Pub/Sub, Pulsar, Kinesis, or similar Help drive the transition from batch processing to event-driven architecture Architecture & Technical Leadership Lead the design of distributed, high-performance systems Establish and promote engineering standards and best practices Ensure scalability, reliability, and security of production systems Mentor engineers and support technical growth across the team Collaborate with product, data, and engineering stakeholders Contribute to technical strategy and modernization initiatives What You Bring ✅ Required Qualifications Strong experience in Java development , with deep expertise in Spring Boot Proven experience building APIs and backend services Hands‑on experience with streaming technologies (Kafka, Pub/Sub, Pulsar, Kinesis, Event Hubs, etc.) Experience designing and building distributed systems and data pipelines Solid understanding of event-driven architecture and real-time processing Demonstrated ability to lead technical initiatives and mentor engineers Nice to Have Experience with Python in data or streaming environments Familiarity with stream processing frameworks (Flink, Spark Streaming) Exposure to AI/ML use cases or integrating AI capabilities into applications Experience with cloud-based data platforms #J-18808-Ljbffr