Job Title:  T&T | EAD | Senior Consultant | NoSQL | Mumbai

The team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.       

Your work profile

1. We are seeking a Real-Time Data & NoSQL Engineer to design, build and optimize high throughput, low latency data platform.
2. Focus on data streaming, caching layer and unstructured storage using Apache Kafka, Redis and MongoDB

 Key Skills required:

• Event Streaming & Messaging (Apache Kafka)
• Design, implement and maintain high throughput Kafka topics, partitions and consumer groups.
• Ensure message delivery guarantees, manage schema evolution using Confluent Schema registry and tune broker/producer configurations for optimal performance.
• Distributed Caching & In-Memory Storage (Redis)
• Design and implement advanced caching patterns to reduce primary database load and latency.
• Utilize Redis data structures (Hashes, Lists, Sets, Sorted Sets, HyperLoglogs, Geospatial) to solve complex application logic at sub-millisecond speeds.
• Configure and manage Redis clusters, sentinel deployments, pub/sub messaging channels and persistent storage configurations.
• NoSQL Document Modeling and Scaling(MongoDB)

• Architect, optimize and maintain large scale MongoDB databases including sharded clusters and replica sets.
• Design efficient BSON document schemas, avoiding anti patterns like unbounded arrays or excessive nesting.

• Perform advanced query optimization, build targeted compound/partial indexes and write complex Aggregation Framework pipelines.
• Profile end to end data flows from Kafka producers through Redis caching layers down to MongoDB persistent storage.
• Troubleshoot bottleneck issues such as consumer lag, cache stampedes, slow queries and memory fragmentation.
• Implement modern data practices.

Preferred Qualifications

• Bachelor’s degree in business, Engineering, Management, or a related field

• Proven track record of executing at least 2 major enterprise-scale database modernization.
• Problem Solving - Exceptional engineering mindset focused on code efficiency.
• Collaboration- Strong ability to work alongside Application developers, DevOps Engineers etc. to coordinate seamless system cutovers.

Location and Way of Working: 

• Base location: Mumbai / 5 days WFO & 2 Saturday’s working