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We are looking for an experienced Technical Lead – Confluent Kafka & Apache Flink to lead the design, development, and implementation of real-time data streaming and event-processing solutions. The ideal candidate will have strong expertise in Apache Kafka, Confluent Platform, Apache Flink, distributed systems, and stream-processing architectures, along with proven technical leadership and stakeholder management skills.

The candidate will be responsible for designing scalable, highly available, fault-tolerant streaming platforms, leading engineering teams, and ensuring the performance, reliability, and security of real-time data pipelines.

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Lead the architecture, design, and implementation of real-time data streaming solutions using Confluent Kafka and Apache Flink.

Design and develop scalable, low-latency, high-throughput event-driven architectures and distributed data-processing systems.

Implement Kafka producers, consumers, topics, partitions, consumer groups, replication, and message-delivery strategies.

Develop and optimize Apache Flink applications for real-time stream processing, stateful computations, event-time processing, and complex event processing.

Design and implement Flink jobs with appropriate checkpointing, savepoints, state management, and fault-tolerance mechanisms.

Manage Kafka clusters, including configuration, performance tuning, monitoring, security, and high availability.

Work with Confluent Platform capabilities such as Schema Registry, Kafka Connect, and stream-processing integrations.

Establish best practices for data governance, schema evolution, data quality, and reliable event delivery.

Troubleshoot complex production issues related to streaming pipelines,



data consistency, latency, throughput, and distributed-system failures.

Collaborate with architects, product owners, DevOps engineers, and business stakeholders to translate requirements into technical solutions.

Lead code reviews, technical discussions, design reviews, and engineering best practices.

Mentor developers and engineers, manage technical deliverables, and ensure timely project execution.

Implement observability, logging, alerting, and performance-monitoring strategies for streaming applications.

Ensure compliance with enterprise security standards, access controls, and operational requirements.

Required Technical Skills

Experience: 13+ years of overall IT experience, with substantial experience in data engineering, distributed systems, and technical leadership.

Confluent Kafka: Strong hands-on experience with Apache Kafka and Confluent Platform.

Apache Flink: Expertise in real-time stream processing, stateful processing, event-time semantics, windowing, and fault tolerance.

Kafka Architecture: In-depth understanding of brokers, topics, partitions, replication, consumer groups, offsets, and delivery semantics.

Programming: Proficiency in Java and/or Scala for developing Kafka and Flink applications.

Kafka Connect: Experience with source and sink connectors and integrating Kafka with databases, APIs, and enterprise systems.

Schema Management: Experience with Confluent Schema Registry and Avro, Protobuf, or JSON Schema.

Distributed Systems: Strong understanding of scalability, fault tolerance, concurrency, consistency,



and high availability.

Performance Optimization: Ability to tune Kafka and Flink applications for throughput, latency, resource utilization, and reliability.

Cloud & Infrastructure: Exposure to AWS, Azure, or GCP, along with containerization and orchestration technologies such as Docker and Kubernetes.

Monitoring & Operations: Experience with metrics, logging, alerting, and production support for distributed streaming platforms.

Leadership: Proven ability to lead technical teams, drive architecture decisions, mentor engineers, and coordinate with stakeholders.

Preferred Qualifications

Experience implementing enterprise-scale event-driven architectures and real-time analytics platforms.

Knowledge of Kafka Streams, ksqlDB, or other stream-processing frameworks.

Experience with CI/CD pipelines, infrastructure automation, and DevOps practices.

Familiarity with data lakehouse platforms, data warehouses, and downstream analytics integrations.

Experience designing disaster recovery, business continuity, and multi-cluster streaming strategies.

Relevant certifications in Confluent, cloud platforms, or data engineering are an advantage.

Leadership & Soft Skills

Strong technical leadership and problem-solving capabilities.

Excellent communication and stakeholder management skills.

Ability to make architecture and technology decisions independently.

Experience managing technical risks, dependencies, and delivery timelines.

Strong documentation, mentoring, and cross-functional collaboration skills.

Engagement Details

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Interested candidates with solid hands-on expertise in Confluent Kafka, Apache Flink, real-time data streaming, and technical leadership are encouraged to apply.

📌 Technical Lead (Confluent Kafka & Apache Flink) | Noida | Onsite | 13+ YOE |Contract : 12 Months | Immediate Joiner
🏢 Codians.ai
📍 Noida