Required Experience & Technical Stack :

- Strong expertise in Java for building scalable data pipelines and microservices, with additional proficiency in Python or Scala as needed for data processing use cases.

- Extensive experience with Java-based big data frameworks, including Apache Spark (Java APIs), Kafka (Java producers/consumers), and Airflow (orchestrated with Java back-end services).

- Strong knowledge of SQL and Java JDBC for querying structured data and integrating with relational databases

- Hands-on experience building microservices in Java, using frameworks such as Spring Boot and Micronaut, including RESTful APIs, service orchestration, and containerization.

- Proficient in Java-based DevOps practices, using tools like Jenkins (Java-based CI), Git, Docker, and Kubernetes to enable scalable CI/CD pipelines.

- In-depth expertise with big data tools, integrating Hive, HBase, and Parquet with Java-based data ingestion and processing solutions.

- Skilled in data transformation and performance tuning using Java multithreading, memory management, and distributed system design patterns.

- Familiarity with integrating Java-based microservices with Machine Learning pipelines, enabling real-time inference and batch processing workflows.

- Architected and scaled high-volume Java microservices, ensuring high availability, resilience, and throughput for enterprise-scale data platforms.

- Strong troubleshooting and debugging capabilities in Java, especially in distributed systems involving asynchronous messaging and parallel computation.

- Experience mentoring engineers in Java best practices, clean code, object-oriented design, and performance optimization for enterprise data solutions.

Candidate Should Be :

- Requires 6+ years of professional experience is essential for understanding system architecture, programming, and technical troubleshooting.

- Outstanding written and verbal communication skills.

- Bachelors/Masters in computer science required