Job Title: Confluent Flink Engineer Experience: 6+ Years Location: Remote Shift Timings: 2:00 PM – 11:00 PM IST Role Overview We are seeking an experienced Confluent Flink Engineer with strong expertise in real-time data streaming, event-driven architectures, and large-scale distributed systems. The ideal candidate should have hands-on experience with Apache Flink, Confluent Kafka, Kafka Streams, and streaming ETL pipelines, along with a strong understanding of cloud-native data processing solutions. The role involves designing, developing, and optimizing real-time streaming applications that process high-volume data efficiently while ensuring scalability, fault tolerance, and performance.

Key ResponsibilitiesStream Processing & Data Engineering Design, develop, and maintain real-time data processing applications using Apache Flink.

Build and manage large-scale streaming ETL pipelines.

Develop event-driven architectures using Confluent Kafka and Kafka Streams.

Implement real-time data transformation, aggregation, enrichment, and analytics workflows. Kafka & Confluent Platform Configure and manage Confluent Kafka environments.

Work with Kafka Connect, Schema Registry, and other Confluent Platform components.

Design productive topic structures, partitioning strategies, and consumer group architectures.

Ensure reliable event processing and message delivery. Performance & Scalability Optimize Flink jobs for performance, throughput, and resource utilization.

Implement checkpointing, state management, and fault-tolerant processing strategies.

Monitor and troubleshoot streaming applications and data pipelines.

Ensure scalability and high availability of streaming platforms. Cloud & DevOps Deploy and manage streaming workloads on AWS, Azure,



or GCP.

Participate in CI/CD pipeline implementation and automation.

Collaborate with DevOps teams to improve deployment, monitoring, and operational practices.

Collaboration

Work closely with Data Engineers, Architects, Product Teams, and Business Stakeholders.

Participate in architecture discussions and technical design reviews.

Contribute to best practices, documentation, and knowledge sharing.

Required Skills & Experience 6+ years of software engineering or data engineering experience.

Strong hands-on experience with Apache Flink.

Extensive experience with Confluent Kafka and Kafka Streams.

Strong understanding of real-time streaming and event-driven architectures.

Experience with distributed systems and large-scale data processing.

Proficiency in Java, Scala, or Python.

Experience building and managing streaming ETL pipelines.

Strong knowledge of

Kafka Connect

Schema Registry

Confluent Platform Components

Strong understanding of

Data Partitioning

State Management

Checkpointing

Fault Tolerance

Experience with AWS, Azure, or GCP cloud platforms.

Familiarity with CI/CD pipelines and DevOps practices.

Preferred Skills Experience with Kubernetes and containerized deployments.

Knowledge of data lake and modern data platform architectures.

Exposure to monitoring tools such as Prometheus, Grafana, or Datadog.

Experience with Spark Streaming or other stream processing technologies.

Key Competencies

Real-Time Data Streaming

Apache Flink Development

Confluent Kafka & Kafka Streams

Distributed Systems

Event-Driven Architecture

Streaming ETL Pipelines

Cloud Data Engineering

Performance Optimization

CI/CD & DevOps Skills: pipelines,etl,data,cloud,devops,processing,kafka,flink

📌 Confluent Flink Engineer (India)
🏢 NSKH Tech
📍 India