- About the job
- Join a fast paced engineering team where you ll help build and optimize data driven solutions that power meaningful business outcomes
- In this role you ll work at the intersection of Java engineering and big data processing with Spark leveraging DBX to deliver scalable reliable pipelines and services
- You ll 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 team-oriented and supportive team culture
Key Responsibilities:
- Key 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
- 3 5 years of hands on experience in software data engineering roles
- Bachelor s or Master s 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 Requirements:
- Spark Java Databricks
Additional Responsibilities:
- 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