Job Description: Senior Java Big Data Developer

Job Title: Senior Java Big Data Developer

Location: Bangalore, Karnataka

Experience: 7+ Years

Employment Type: Full-Time

Work Mode: Hybrid / Work from Office

Job Summary: We are seeking a highly skilled Senior Java Big Data Developer with 7+ years of experience in designing, developing, and implementing large-scale enterprise applications and Big Data solutions. The ideal candidate should possess strong expertise in Core Java, Spring Framework, Java/J2EE, Hadoop Ecosystem technologies, and Apache Spark. The candidate will be responsible for developing scalable data processing applications, optimizing big data workflows, integrating multiple data sources, and supporting enterprise analytics initiatives.

Key Responsibilities:

- Design, develop, and maintain enterprise-grade applications using Core Java, Java/J2EE, and Spring Framework.

- Build scalable Big Data solutions using Hadoop and Spark technologies.

- Develop and optimize data processing pipelines for large datasets.

- Work with distributed computing frameworks and big data platforms.

- Design and implement ETL and data transformation processes.

- Develop RESTful APIs and microservices using Spring Boot.

- Collaborate with architects, business analysts, and data engineering teams to define technical solutions.

- Optimize application and query performance for high-volume data processing.

- Perform code reviews, debugging, and troubleshooting.

- Ensure adherence to coding standards, security practices, and best development methodologies.

- Participate in Agile ceremonies including sprint planning, reviews, and retrospectives.

- Support production deployments and resolve critical issues.

Required Technical Skills:

1. Java Technologies:

- Core Java

- Java/J2EE

- Spring Framework

- Spring Boot

- Spring MVC

- RESTful Web Services

- Microservices Architecture

- Multithreading

- Collections Framework

- Design Patterns

2. Hadoop Ecosystem:

- Strong hands-on experience with: Hadoop, HDFS (Hadoop Distributed File System), Hive, HBase, MapReduce, Pig, Sqoop, YARN.

3. Apache Spark:

- Spark Core, Spark SQL, Spark Streaming, DataFrame & Dataset APIs, Spark Performance Optimization, Distributed Data Processing.

4. Database Technologies:

- SQL, Oracle, MySQL, PostgreSQL, NoSQL Databases (Preferred).

5. Data Engineering:

- ETL Development, Data Transformation, Data Integration, Data Warehousing Concepts, Batch & Real-Time Processing.

6. Cloud & DevOps (Preferred):

- AWS / Azure / GCP, Docker, Kubernetes, Jenkins, CI/CD Pipelines, Git.

Required Qualifications:

- Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field.

- 7+ years of software development experience.

- Strong hands-on experience in Java/J2EE technologies.

- Extensive experience with Hadoop ecosystem tools and Apache Spark.

- Experience developing large-scale distributed applications.

- Strong understanding of object-oriented programming concepts and design patterns.

- Experience working in Agile development environments.

Preferred Qualifications:

- Experience with Kafka or other messaging platforms.

- Knowledge of Data Lake and Data Warehouse architectures.

- Exposure to cloud-native data engineering solutions.

- Hadoop or Spark certifications.

- Experience with machine learning data pipelines is an added advantage.

Soft Skills:

- Strong analytical and problem-solving abilities.

- Excellent communication and stakeholder management skills.

- Ability to work independently and collaboratively.

- Strong debugging and troubleshooting skills.

- High ownership and accountability.

- Ability to handle multiple priorities in a fast-paced environment.

Key Competencies:

- Core Java, Java/J2EE, Spring Framework, Spring Boot, Hadoop Ecosystem, HDFS, Hive, HBase, MapReduce, Pig, Sqoop, Apache Spark, ETL Development, Data Engineering, Microservices Architecture.

Work Location: Bangalore, Karnataka.

Candidates with strong Java development expertise, Big Data experience, and hands-on knowledge of Hadoop and Spark technologies are encouraged to apply.