Job Description:

Join a data driven team where your work with distributed processing helps turn complex datasets into meaningful insights
In this role you ll collaborate closely with engineers analysts and stakeholders to build reliable scalable data solutions using Spark contributing to faster decision making and better customer outcomes
You ll be encouraged to take ownership of deliverables improve performance and bring clarity to ambiguous problem statements through structured analysis and thoughtful implementation
If you enjoy solving large scale data challenges optimizing pipelines and working in a collaborative environment that values learning and continuous improvement this opportunity will help you grow your technical depth while making a visible impact across projects and teams

Key Responsibilities:

Key Responsibilities
Design develop and maintain scalable data processing jobs using Spark for batch and or near real time workloads
Analyze large datasets to identify trends anomalies and data quality issues implement validation and reconciliation checks
Optimize Spark applications for performance by tuning partitions caching strategies memory usage and execution plans
Collaborate with cross functional teams to translate business requirements into technical solutions and well defined deliverables
Implement robust error handling logging and monitoring to ensure reliability and easier troubleshooting
Participate in code reviews follow engineering best practices and contribute to reusable components and standards
Support deployments and production issues by performing root cause analysis and implementing preventive fixes

Minimum Qualifications
Bachelor s degree or equivalent in Engineering Technology Computer Science or related field BTech BE MSc or equivalent
5 years of experience working on data engineering or big data processing initiatives
Hands on experience building and maintaining Spark based data processing solutions
Strong understanding of distributed computing concepts and data processing fundamentals
Ability to work independently on assigned modules and collaborate effectively within a team
Preferred Qualifications
Master s degree MTech MCA or equivalent in a relevant discipline
Proven experience delivering end to end Spark pipelines including development testing and production support
Experience improving job performance and stability through Spark tuning and structured troubleshooting practices
Familiarity with building reusable frameworks components to standardize Spark development across projects
Strong communication skills to explain technical trade offs and align solutions with stakeholder expectations
Good to have skills
Hadoop Hive Kafka Airflow Delta Lake

Technology->Java->Apache->Spark,Technology->Data Engineering->Spark->Spark Sreaming