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At Zensar, we're "experience-led everything". We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we're a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

Required Skills & Experience

Must Have

• 3+ years hands-on experience with Apache Kafka / Confluent Platform / Confluent Cloud

• Strong experience with Kafka Connect - deploying, configuring, and managing connectors (both self-managed and Confluent Managed)

• Experience migrating from custom/self-managed connectors to Confluent Managed Connectors

• Proficiency with Schema Registry and schema evolution strategies

• Experience with at least 3 of the following connectors: S3 Sink/Source, JDBC Source/Sink, Debezium CDC, HTTP/REST Source/Sink, Oracle CDC

• Solid understanding of Kafka internals: partitioning, replication, consumer groups, offset management

• Experience with Infrastructure as Code (Terraform, Ansible) for Kafka/Confluent resource provisioning

• Proficiency in at least one of: Java, Python, or Go for custom connector development or Kafka Streams

• Experience with CI/CD pipelines for connector deployment and configuration management

• Strong troubleshooting skills for distributed systems

Nice to Have

• Confluent Certified Developer or Administrator certification

• Experience with ksqlDB for stream processing

• AWS ecosystem experience (S3, MSK, Lambda, EventBridge)

• Experience with Oracle integration (ORBC, OCI, ORDS)

• Familiarity with data mesh or event-driven architecture patterns

• Experience with Confluent Cloud Cluster Linking or Schema Linking

• Knowledge of RBAC/ACL configuration in Confluent Platform

• Experience with retail or supply chain domain data

Technical Environment

• Confluent Cloud / Confluent Platform

• Apache Kafka, Kafka Connect, Schema Registry, ksqlDB

• AWS (S3, EC2, IAM, CloudWatch)

• Terraform / Infrastructure as Code

• Git, CI/CD (Jenkins, GitHub Actions, or similar)

• Monitoring: Confluent Control Center, Prometheus, Grafana, Datadog

• Oracle ORBC, REST APIs, ORDS (integration source systems)

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or related field (or equivalent experience)

• Minimum 5 years overall experience in data engineering or integration roles

• Minimum 3 years focused Confluent/Kafka experience

• Strong communication skills - ability to work with architecture teams and business stakeholders

Key Responsibilities

• Design, develop, and maintain Kafka-based data integration pipelines using Confluent Platform / Confluent Cloud

• Migrate existing custom connectors to Confluent Managed Connectors (S3 Sink/Source, JDBC, Debezium, REST, etc.)

• Configure, deploy, and monitor Kafka Connect clusters and connector instances

• Implement Schema Registry governance (Avro, JSON Schema, Protobuf) for data contracts

• Build and optimise Kafka Streams or ksqlDB applications for real-time data transformation

• Collaborate with the EIDH architecture team on integration patterns (event-driven, CDC, batch offload)

• Troubleshoot connector failures, consumer lag, partition rebalancing, and throughput issues

• Implement observability: monitoring, alerting, and dashboarding for Kafka ecosystem components

• Support data governance, lineage, and security (ACLs, RBAC, encryption in transit/at rest)

• Participate in incident response and production support for streaming infrastructure