Java AWS developer

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

We are seeking a highly skilled Kafka Migration Engineer with on-prem Apache Kafka to AWS MSK migration experience. This role will focus on cluster discovery, topic mapping, capacity planning, platform configuration, migration execution, validation, performance tuning, automation, and legacy cluster decommissioning. The ideal candidate will bring strong hands-on engineering experience with distributed messaging systems, a structured delivery mindset, and the ability to collaborate effectively with application, infrastructure, and platform teams to execute migrations safely and at scale.

Key skills required:

▪Assess on-prem Kafka clusters and perform discovery across topics, partitions, consumer groups, throughput patterns, retention policies, and inter-service dependencies to determine migration readiness.

▪Analyze workloads based on message volume, business criticality, ordering guarantees, latency requirements, and consumer group complexity to determine appropriate MSK cluster placement and configuration.

▪Plan and provision required AWS MSK infrastructure capacity including broker sizing, storage, networking, and security configurations to support migration, testing, and production execution.

▪Execute UAT and production parallel testing using MirrorMaker 2 or similar replication tooling, compare message delivery outcomes, capture evidence, and troubleshoot discrepancies through closure.

▪Perform performance tuning and optimization of MSK clusters to ensure migrated workloads are stable, scalable, efficient, and production ready.

▪Partner with application engineering, infrastructure, and platform teams to finalize migration plans, consumer/producer cutover approach, validation criteria, and rollback considerations.

▪Manage release readiness, execute production cutover activities including consumer group migration, offset synchronization, and complete post-release checkout and validation procedures.

▪Support legacy on-premises Kafka cluster decommissioning after successful migration and validation.

▪Design, enhance, and implement automation frameworks and AI-assisted solutions to enable repeatable, efficient, large-scale Kafka-to-MSK migrations.

▪Document migration procedures, operational learnings, risks, and best practices to improve the factory execution model.

Preferred Qualifications

• Education - Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline

• 4.5 - 7 years of hands-on engineering experience in a collaborative, team-based environment with distributed messaging systems.

Key Skills & Competencies

▪AWS Services: Hands-on experience with AWS compute and migration patterns, including ECS, EKS, Lambda, CloudWatch, and related cloud services.

▪Apache Kafka: Deep hands-on experience with Kafka architecture including brokers, topics, partitions, consumer groups, replication, and cluster operations.

▪AWS MSK: Practical experience with Amazon Managed Streaming for Apache Kafka including cluster provisioning, configuration, monitoring, and security (IAM, mTLS, SASL/SCRAM).

▪Migration Tooling: Experience with MirrorMaker 2, Confluent Replicator, or similar cross-cluster replication tools for data migration and offset synchronization.

▪Cloud Migration: Practical understanding of on-prem to cloud migration strategies, workload assessment, testing, cutover, and post-migration validation.

▪Kafka Ecosystem: Familiarity with Schema Registry, Kafka Connect, Kafka Streams, and related ecosystem components.