Data Engineer - Java +Spark | Immediate Joiner | Pan India Hiring

UST; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

UST in Bengaluru, India, is seeking a Data Engineer to design and build scalable, cloud-native data pipelines using Java, Spark, Airflow, and GCP. You will develop distributed data processing pipelines, create Airflow DAGs, leverage BigQuery and Cloud Storage, and write optimized SQL queries to transform data.

The role emphasizes reliability, performance, and collaboration with engineering and analytics teams.

Qualifications

• Strong hands-on experience with Java and Apache Spark.
• Proficiency in Apache Airflow DAG authoring.
• Experience with GCP services including BigQuery and Cloud Storage.
• Good understanding of data pipeline orchestration and cloud-native data engineering.

Responsibilities

• Develop and optimize distributed data processing pipelines using Java-based Apache Spark.
• Design and maintain Apache Airflow DAGs for data pipeline orchestration and scheduling.
• Work with GCP services including BigQuery and Cloud Storage to build scalable data solutions.
• Write and optimize complex SQL queries for data transformation and analysis.
• Apply data engineering best practices around pipeline reliability, scalability, monitoring, and performance.
• Collaborate with engineering and analytics teams to deliver high-quality data solutions.

Skills

Java

Apache Spark

SQL

Data pipeline design

Cloud-native architecture

Tools

Apache Airflow

BigQuery

Cloud Storage

Job description

We are looking for a Data Engineer with strong experience in Java, Apache Spark, Apache Airflow, and GCP to design and build scalable, cloud-native data pipelines.

Key Responsibilities & Skills:

• Develop and optimize distributed data processing pipelines using Java-based Apache Spark.
• Design and maintain Apache Airflow DAGs for data pipeline orchestration and scheduling.
• Work with GCP services including BigQuery and Cloud Storage to build scalable data solutions.
• Write and optimize complex SQL queries for data transformation and analysis.
• Apply data engineering best practices around pipeline reliability, scalability, monitoring, and performance.
• Collaborate with engineering and analytics teams to deliver high-quality data solutions.

Must-Have Skills:

• Strong hands-on experience with Java + Apache Spark.
• Proficiency in Apache Airflow / DAG authoring.
• Experience with GCP – BigQuery and Cloud Storage.
• Good understanding of data pipeline orchestration and cloud-native data engineering.

Preferred Experience:

Experience with large-scale data processing, performance optimization, and production-grade data pipelines.