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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