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.

Roles 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.

Technical Requirement
Minimum Qualifications:

- Bachelor's degree (or equivalent) in Engineering/Technology/Computer Science or related field (BTech/BE/MSc or equivalent).

- 3-5 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.
Valuable to have skills:
Hadoop, Hive, Kafka, Airflow, Delta Lake

Additional Responsibility
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
Infosys provides equal employment opportunities to applicants and employees without regard to race, color, sex, gender identity; sexual orientation, religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.

Educational Requirement
Bachelor of Engineering,Bachelor Of Technology

Preferred Skills
Technology->Data Engineering->Spark->SparkSQL,Technology->Java->Apache->Spark

Service Line
Data Analytics Unit

📌 Spark Developer (Bengaluru)
🏢 Infosys
📍 Bengaluru