Spark-Java, DBX

Infosys; Bengaluru; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

Infosys in Bengaluru is seeking a Java and Spark expert to design, develop, and optimize data-driven solutions powering business outcomes. You will work at the intersection of Java engineering and big data processing with Spark and DBX to deliver scalable pipelines and services.

You will collaborate with data engineers, platform teams, and stakeholders to translate requirements into well-structured implementations, improve performance, and strengthen data quality while taking ownership from

Qualifications

• 35 years of hands-on experience in software/data engineering.
• Strong programming experience in Java with solid understanding of OOP and coding best practices.
• Practical experience with Apache Spark for batch data processing and ETL pipelines; working knowledge of DBX.

Responsibilities

• Design, develop, and maintain Spark-based data processing jobs using Java aligned to business and technical requirements.
• Build and enhance ETL workflows, ensuring accuracy, completeness, and consistency of processed datasets.
• Implement integrations and workflows on DBX, supporting scalable execution and operational reliability.
• Optimize Spark jobs for performance (partitioning, caching, shuffle tuning) and cost efficiency.
• Write clean, maintainable code with appropriate logging, error handling, and unit/integration tests.
• Troubleshoot production issues, perform root-cause analysis, and implement preventive fixes.
• Collaborate with cross-functional teams to refine requirements, plan deliveries, and ensure smooth releases.
• Document technical designs, data flows, and operational runbooks to support long-term maintainability.

Skills

Java

Apache Spark

ETL

Data pipelines

Education

B.Tech / M.Tech / MCA / MSc

Tools

DBX

Databricks

Job description

Job DescriptionAbout the job:

Join a fast-paced engineering team where youll help build and optimize data-driven solutions that power meaningful business outcomes. In this role, youll work at the intersection of Java engineering and big data processing with Spark, leveraging DBX to deliver scalable, reliable pipelines and services. Youll collaborate closely with data engineers, platform teams, and stakeholders to translate requirements into well-structured implementations, improve performance, and strengthen data quality. If you enjoy solving complex problems, working with modern data platforms, and taking ownership from design to delivery, this is a great opportunity to grow your impact while learning from a collaborative and supportive team culture.

Roles ResponsibilitiesKey Responsibilities:

• Design, develop, and maintain Spark-based data processing jobs using Java aligned to business and technical requirements.
• Build and enhance ETL workflows, ensuring accuracy, completeness, and consistency of processed datasets.
• Implement integrations and workflows on DBX, supporting scalable execution and operational reliability.
• Optimize Spark jobs for performance (partitioning, caching, shuffle tuning) and cost efficiency.
• Write clean, maintainable code with appropriate logging, error handling, and unit/integration tests.
• Troubleshoot production issues, perform root-cause analysis, and implement preventive fixes.
• Collaborate with cross-functional teams to refine requirements, plan deliveries, and ensure smooth releases.
• Document technical designs, data flows, and operational runbooks to support long-term maintainability.

Minimum Qualifications:

• 35 years of hands-on experience in software/data engineering roles.
• Bachelors or Masters degree: BTECH, MTECH, MCA, MSC.
• Strong programming experience in Java with solid understanding of OOP and coding best practices.
• Practical experience with Apache Spark for batch data processing.
• Experience building and supporting ETL pipelines and data transformations.
• Working knowledge of DBX for developing and running data workflows.

Technical RequirementSpark-Java, Databricks

Additional ResponsibilityPreferred Qualifications:

Preferred Qualifications:

• Experience designing end-to-end data pipelines including ingestion, transformation, validation, and publishing layers.
• Strong understanding of distributed processing concepts and Spark internals for performance tuning and stability.
• Exposure to CI/CD practices for data/engineering workflows and disciplined release management.
• Experience with production monitoring, alerting, and operational support for data pipelines.
• Proven ability to collaborate with stakeholders, communicate trade-offs, and deliver within timelines.

Educational RequirementMCA,MSc,MTech,Bachelor of Engineering,BTech

Preferred SkillsTechnology->Java->Apache->Spark,Technology->Data Engineering->Databricks

Service LineData Analytics Unit