Big Data Engineer

Strong hands-on experience with Google Cloud Platform (GCP)
Proven expertise in batch and real-time data pipelines
Programming experience in Python 
Hands-on experience with BigQuery, Bigtable, Pub/Sub, Dataflow, and Cloud Composer
Strong understanding of Spark concepts and optimization techniques
Must have proficiency to code data transformations in Spark using any programming language (Python / Java / Scala)
Proficiency with SQL syntax and queries with medium complexity

Core Java: Well versed with OOP, Data Structures, Generics, Collections, Basic understanding of Spring: Core & REST API

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

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.

• 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

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

• 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]

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

• 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)

• 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