Data Engineer - Google Cloud Platform

Job Title : Hiring: Data Engineer

Experience : 5-8 Years

Location : Bangalore

Joining : Immediate Joiners Preferred

About the Role :

We are looking for a skilled and experienced Data Engineer to design, build, and optimize scalable data solutions on cloud platforms. The ideal candidate should have strong expertise in GCP services, distributed data processing frameworks, backend development, and modern cloud-native architectures.

Key Responsibilities :

- Design, build, and maintain scalable data pipelines using GCP services such as Dataflow, Pub/Sub, and BigQuery.

- Modernize and migrate legacy data workflows into cloud-native architectures.

- Develop and optimize distributed data processing systems using Spark and the Hadoop ecosystem.

- Integrate Salesforce with external systems using APIs and event-driven integration patterns.

- Collaborate with cross-functional teams on data modeling, ingestion, synchronization, and transformation processes.

- Develop backend services and APIs using Java and Spring Boot.

- Ensure high performance, reliability, scalability, and monitoring of data pipelines and applications.

- Implement containerization and deployment strategies using Docker and Kubernetes.

- Support CI/CD implementation and deployment automation for data and backend applications.

- Troubleshoot production issues and optimize system performance.

Required Skills & Qualifications :

- 5-8 years of experience in Data Engineering or related roles.

- Strong hands-on experience with GCP services including Dataflow, Pub/Sub, and BigQuery.

- Expertise in distributed data processing frameworks such as Spark and Hadoop.

- Good understanding of cloud-native architecture and data modernization strategies.

- Experience integrating Salesforce with enterprise systems using REST/SOAP APIs and event-driven architectures.

- Strong programming skills in Java and hands-on experience with Spring Boot.

- Experience with Docker, Kubernetes, and CI/CD pipelines.

- Strong understanding of data modeling, ETL/ELT processes, and scalable data architectures.

- Familiarity with monitoring, logging, and performance optimization tools.

- Excellent problem-solving and collaboration skills.

Success Metrics :

- Delivery of scalable, secure, and reliable data pipelines.

- Successful modernization and migration of legacy workflows.

- Efficient and seamless integration of enterprise data systems.

- High-performance backend services and optimized data processing workflows.