Data Engineer – Java & Apache Spark | 7 YoE | Any UST Location | Immediate Joiner

UST; Bengaluru; On-site; INR 1,200,000 - 1,600,000; Full time

Job summary

UST in Bengaluru seeks a skilled Java/Spark developer to build and optimize distributed data processing applications. You will work on large-scale data pipelines, leveraging Spark APIs and SQL to ensure performance and reliability.

Ideal candidates have strong Java fundamentals, experience with Hadoop ecosystems, and familiarity with cloud platforms. Join a dynamic team delivering cutting-edge data solutions in a fast-paced environment.

Qualifications

• Strong hands-on development experience with Core Java.
• Practical experience in distributed data processing using Apache Spark.
• Experience with Spark APIs in Java.
• Strong SQL skills including complex queries, joins, transformations, and performance optimization.
• Solid understanding of OOP, collections, multithreading, exception handling, and Java fundamentals.
• Experience troubleshooting and optimizing high-volume data processing workloads.

Responsibilities

• Develop scalable data processing applications using Java and Spark.
• Collaborate with data engineering teams to optimize ETL pipelines.
• Tune and troubleshoot performance issues in large-scale data workloads.

Skills

Core Java

Apache Spark

Spark APIs

SQL

OOP/Collections/Multithreading

High-volume data processing

Tools

Kafka

Hadoop/HDFS

Azure/AWS/GCP

Databricks

CI/CD/DevOps

Relational and NoSQL databases

Job description

Mandatory Skills

• Core Java – Strong hands-on development experience
• Apache Spark – Strong practical experience developing distributed data processing applications
• Spark with Java / Spark APIs
• SQL – Complex queries, joins, transformations, and performance optimization
• Strong understanding of OOP, Collections, Multithreading, Exception Handling, and Java fundamentals
• Experience troubleshooting and optimizing high-volume data processing workloads

Good to Have

• Experience with Kafka
• Exposure to Hadoop/HDFS
• Experience with cloud platforms such as Azure, AWS, or GCP
• Knowledge of Databricks
• CI/CD and DevOps exposure
• Experience working with relational and NoSQL databases