Role Summary :

The Senior Streaming Data Developer / Confluent Lead is responsible for designing, developing, governing, and supporting enterprise-scale event streaming and real-time data processing solutions using the Confluent Platform and Apache Kafka ecosystem.

This role combines deep hands-on engineering expertise with architectural leadership to deliver scalable, secure, resilient, and high-performing streaming data solutions.

The candidate will work closely with enterprise architects, platform teams, business stakeholders, and delivery partners to drive adoption of event-driven and real-time streaming architectures across the organization.

The ideal candidate should possess strong practical experience with Confluent Managed Services, Apache Flink, SQL-based stream processing, and Kafka ecosystem tooling, while also being capable of guiding enterprise-level streaming strategy and implementation standards.

Experience Required :

812 years of overall IT experience with at least 6 years of hands-on experience in :

- Confluent Platform / Apache Kafka
- Real-time event streaming solutions
- Streaming data engineering and processing
- Strong hands-on experience with Confluent Cloud / Confluent Managed Services
- Proven experience designing and implementing enterprise-scale event-driven architectures
- Solid practical experience with Apache Flink for stateful stream processing, event enrichment, event generation, windowing, and real-time analytics
- Strong SQL expertise (mandatory), particularly for Flink SQL and streaming transformations
- Experience migrating or modernizing streaming solutions from KSQL/ksqlDB to Flink-based implementations




- Experience working within large, complex enterprise integration and data ecosystems
- Experience working with managed connectors and custom connector development

Key Responsibilities :

1.

Streaming

Architecture &

- Platform Leadership :
- Define and govern target-state architecture for Kafka and Confluent-based event streaming platforms
- Provide technical leadership for enterprise streaming initiatives and real-time data integration programs
- Validate solution direction and provide strategic guidance to business and technology stakeholders
- Support client teams in defining scalable and maintainable streaming data patterns

2. Hands-on Development &

- Engineering :
- Develop and support Kafka producers, consumers, Kafka Connect integrations, and Flink streaming applications
- Design and implement real-time data transformation and enrichment pipelines using Flink and SQL
- Build and customize Kafka connectors where managed connectors do not meet business requirements
- Provide hands-on troubleshooting, performance tuning, and optimization for Kafka and Flink workloads
- Support migration and transformation approaches from KSQL/ksqlDB to Apache Flink

3. Data Governance &

- Streaming Standards :
- Establish and govern topic design,



naming conventions, schema governance, event lifecycle, and data contracts
- Define and manage append vs upsert topic strategies, Avro/JSON schema registry, and compatibility rules
- Ensure streaming data solutions align with enterprise architecture, security, and governance standards

4.

Platform

Reliability &

- Operations :
- Provide guidance on high availability, disaster recovery, scalability, and resiliency
- Support Confluent Managed Services operations and platform governance
- Collaborate with cloud, DevOps, data engineering, and integration teams for consistent platform adoption

Required Skills &

- Technical Expertise :

Core Streaming Technologies :

- Confluent Platform / Confluent Cloud, Apache Kafka, Apache Flink, Kafka Connect, Schema Registry, REST Proxy, ksqlDB

Kafka &

- Streaming Concepts :
- Producers/Consumers, Partitions/Replication, Consumer Groups, Offset Management, Topic Compaction, Exactly-once processing, Event-driven architecture

Flink &

- Stream Processing :
- Flink SQL, Stateful stream processing, Stream joins, Windowing, Event-time processing

Data &

- Schema Management :
- SQL expertise, Avro/JSON schemas, Schema evolution, CDC patterns

Cloud &

- Platform Engineering :
- Kafka in cloud/Kubernetes, CI/CD, Infrastructure-as-Code, performance tuning

Soft Skills :

- Strong stakeholder communication, documentation, and governance capabilities

Preferred Experience :

- Multi-region Kafka deployments, enterprise data/AI platform integration, regulated environments, CDC, certifications

📌 Senior Streaming Data Developer (India)
🏢 DataQuad
📍 India