Data Engineer – GCP Java & Big Data

Job Summary

We are looking for skilled GCP Data Engineers with 6–9 years of hands-on experience in building scalable, high-performance data solutions. The ideal candidate will have strong expertise in Java-based big data processing frameworks and deep exposure to Google Cloud Platform (GCP) services for modern data engineering workloads.

Key Skills & Experience

• Strong programming expertise in Java, with experience in building distributed data processing applications
• Hands-on experience with Big Data technologies such as Apache Spark (Java/Scala APIs), Hadoop, and Hive
• Experience with Spark (DataFrame/Spark SQL) using Java or Scala (PySpark knowledge is a plus but not primary)
• Solid understanding of data structures, algorithms, and object-oriented programming in Java
• Strong knowledge of SQL, data modeling, and data warehousing concepts
• Experience working with Linux/Unix environments and scripting (Bash or similar)
• Proven analytical and problem-solving skills, especially in debugging and optimizing data pipelines
• Ability to design and build scalable, fault-tolerant data processing systems
  
  

Preferred / Good To Have

• Hands-on experience with GCP services such as BigQuery, Dataflow (Apache Beam with Java), Dataproc, Cloud Storage, Pub/Sub, and IAM
• Experience with workflow orchestration tools like Airflow or Cloud Composer
• Exposure to cloud migration projects, especially transitioning from on-premise Hadoop ecosystems to GCP
• Familiarity with streaming data pipelines using Pub/Sub and Dataflow
• Understanding of CI/CD pipelines and DevOps practices in a cloud environment
  
  

Roles & Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Java-based big data frameworks on GCP
• Build and optimize batch and streaming data processing solutions using Dataproc, Dataflow, and Spark
• Ensure high-quality, efficient, and maintainable code by following best practices and coding standards
• Perform unit testing, integration testing, and troubleshoot complex data pipeline issues
• Collaborate with cross-functional teams to understand data requirements and deliver robust solutions
• Estimate development efforts and contribute to sprint planning and delivery
• Participate in code reviews and mentor junior team members where required
• Design cost-optimized and performance-efficient architectures leveraging GCP-native services
  
  

GCP, Pyspark, Java, SQL

Skills : Java, Bigdata ,GCP

Core Java: Well versed with OOP, Data Structures, Generics, Collections, Basic Regular Expressions, IO, Basic Concurrency. Java Spring: Core, REST API's Knowledge of: Basics Shell scripting, Postman, JSON, MYSQL Big Data: Hadoop, Map reduce, Basic Spark, HBase(M7) GCP skillset, Big query

a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; }

We are looking for a skilled Software Engineer / Data Engineer with strong expertise in Core Java, Big Data technologies, and GCP to design, develop, and maintain scalable data processing systems and microservices.

Primary Skills / Technical Expertise

Core Java

• Strong knowledge of OOP concepts, Data Structures & Algorithms
• Expertise in Collections, Generics, Exception Handling
• Experience in Multithreading & Basic Concurrency
• Hands-on with Java IO & file processing
• Understanding of Regular Expressions
  
  

Java & Spring Framework

• Experience in Spring Core, Spring Boot
• Strong exposure to REST API design and development
• Knowledge of Microservices architecture
  
  

Big Data Technologies

• Hands-on experience with:
• Hadoop Ecosystem
• MapReduce
• Apache Spark (Core & Basics of Spark SQL/PySpark)
• Hive (good to have)
• HBase or other NoSQL systems
• Understanding of:
• Distributed computing concepts
• Batch & real-time data processing pipelines
• Ability to handle large-scale data (GBs to TBs) (typical in Big Data roles) [Round 2 MI...Recording | Video]
  

GCP (Google Cloud Platform)

• Hands-on experience with:
• BigQuery
• Cloud Storage (GCS)
• Good to have:
• Dataflow / Dataproc
• Pub/Sub
• Understanding of cloud-based data pipelines and deployment
  

Database / Tools

• Strong knowledge of:
• SQL (MySQL / Hive / BigQuery queries)
• JSON handling & API integration
• Tools:
• Postman (API testing)
• Shell scripting (basic automation)
• Version control tools (Git – optional but preferred)
  

Key Responsibilities

• Design and develop scalable data processing applications
• Build and optimize ETL/data pipelines for large datasets
• Develop and maintain REST APIs and microservices
• Work on Big Data transformations and storage solutions
• Integrate systems with GCP cloud services
• Perform data validation, testing, and performance tuning
• Collaborate with cross-functional teams for end-to-end delivery