Full Stack Engineer

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

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