12+ years of experience delivering data-intensive solutions (data technical architect and engineering).
Streaming and event driven data experience building and utilizing Kafka or queue-based architectures including ordering, replay, schema evolution, and real time observability.
Strong hands-on expertise in Apache Kafka ecosystem including Kafka Connect, Kafka Streams (KStreams), ksqlDB, schema registry, producer/consumer services using Java.
Strong understanding of transactional integrity, idempotency, and error handling in financial data flows. Hands-on experience building Java/Spring Bootbased data processing services that produce and consume Kafka events, apply realtime transformations and enrichment, and persist channeloptimized views into MongoDB to support lowlatency omnichannel banking use cases.
Experience designing replay safe and resilient consumers for banking workloads.
Proven experience implementing and architecting Change Data Capture (CDC) data from heterogeneous sources (RDBMS, NoSQL, SaaS) using tools like Debezium, Goldengate, or native connectors.
Solid understanding of MongoDB, Schema design & document modeling, Indexing, sharding techniques and performance tuning. Good to have experience in Azure cosmos for mongo db vCore architecture.
Hands-on experience designing MongoDB as a realtime, readoptimized data serving layer, decoupled from systems of record, for mobile and omnichannel banking use cases.
Performance tuning for lowlatency mobile workloads.
Hands-on expertise in architecting omnichannel and Customer 360 data platforms using MongoDB or similar NoSQL databases. Experience building eventdriven materialized views in MongoDB to support mobile apps, web.
Strong knowledge of stream and batch processing frameworks such as Spark, Flink, and cloud-native/on-prem data processing services.
Expertise in modern data architecture including data mesh, and unified data platforms across onprem and cloud (Azure/AWS/GCP).
Strong knowledge of APIled and eventdriven architectures working together (REST + async events). Ability to define contracts, versioning, backward compatibility, and domain events aligned to banking domains.
Hands-on experience building Java / Spring Boot services that consume Kafka events and persist realtime, replaysafe updates into MongoDB.
Strong understanding of APIdriven architectures and how they integrate with streaming and event platforms.

Principal Streaming Data Architect for our banking client in Chennai

Optimum Solutions Pte Ltd

Job Description

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