Java) - Onsite Hybrid

NTT DATA Services•Cupertino, CA

5d•$96,492 - $144,738•Hybrid

About The Position

Join a team building next-generation, cloud-native data platforms powering real-time and batch data movement at enterprise scale. You will design and develop streaming and batch frameworks, Kafka/Flink/Spark-based processing engines, and cloud-native solutions on Azure and Kubernetes. Ideal candidates have strong distributed systems experience and a passion for platform engineering, automation, and data modernization.

Requirements

Minimum 8+ years of overall Software Engineering or Data Engineering experience.
Minimum 5+ years of hands-on experience with Apache Spark for large-scale batch and streaming data processing.
Minimum 5+ years of hands-on experience with Apache Kafka including event-driven architectures and real-time data streaming solutions.
Minimum 3+ years of hands-on experience with Apache Flink for stream processing and real-time analytics workloads.
Minimum 5+ years of experience developing applications using Java and/or Scala.
Minimum 5+ years of experience writing complex SQL queries and optimizing database performance.
Minimum 3+ years of experience with Kubernetes and containerized application deployment.
Minimum 3+ years of experience designing and implementing solutions on Microsoft Azure Cloud.
Minimum 3+ years of experience building and supporting distributed data platforms using Cassandra, YugabyteDB, PostgreSQL, or similar databases.
Minimum 3+ years of experience building event-driven architectures and streaming applications.
Minimum 2+ years of experience implementing CI/CD pipelines, source control, and deployment automation using GitLab, GitHub, or similar tools.
Minimum 2+ years of experience with cloud-native deployment patterns, containerization, and platform automation.

Nice To Haves

Demonstrated experience in performance tuning, troubleshooting, and supporting mission-critical data platforms.
Experience with Apache Airflow orchestration.
Experience with metadata-driven data platforms and self-service ingestion frameworks.
Experience with enterprise cloud migration and modernization programs.
Experience with platform engineering and internal developer platforms.
Experience leading technical initiatives, mentoring engineers, or serving as a technical lead.
Knowledge of DevSecOps, infrastructure as code, and observability frameworks.

Responsibilities

Design, develop, and support scalable real-time and batch data pipelines using Apache Spark, Apache Flink, Apache Kafka, and Airflow.
Build and enhance metadata-driven self-service data integration platforms and reusable connectors.
Develop and maintain source and target connectors for relational databases, file systems, Kafka, Cassandra, YugabyteDB, and other enterprise data stores.
Design, deploy, and operate Kubernetes-based streaming and batch processing platforms.
Lead cloud migration initiatives from on-premise environments to Microsoft Azure.
Drive performance tuning, scalability optimization, reliability improvements, and operational excellence across large-scale data workloads.
Develop cloud-native solutions supporting enterprise data movement and processing.
Collaborate with product owners, architects, cloud engineering teams, and business stakeholders to deliver enterprise-scale data solutions.
Contribute to platform modernization, automation, CI/CD implementation, and engineering best practices.
Support troubleshooting, production stability, and continuous improvement initiatives for critical data platforms.