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NSDL Payments Bank logo — NSDL Payments Bank Real-Time Streaming Intern in Pune, Maharashtra
NSDL Payments Bank VerifiedActively Hiring

Real-Time Streaming Intern

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Location

Pune, Maharashtra

Work Mode

Hybrid

Duration

2 months

Stipend

₹18,000/mo

Start Date

Immediate / Rolling

Openings

14 positions

Type

Full-time

Category

Data Science

Apply Now — ₹18,000/moApply on Company Website ↗

About the Internship

Join NSDL Payments Bank in Pune as a Real-Time Streaming Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on real-time data processing work. About the role As a Real-Time Streaming Intern at NSDL…

About NSDL Payments Bank

NSDL Payments Bank offers a mentor-led Real-Time Streaming Intern in Pune with live project work in data science, a stipend of ₹18,000/month and a Pre-Placement Offer opportunity for strong performers.
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Pune, MaharashtraVerified employer14 openings
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Skills Required

Stream ProcessingApache KafkaSpark Streaming or FlinkWindowingEvent Time vs Processing TimePython or JavaSQLMonitoringBackpressureGit

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), BCA/MCA or B.Sc/M.Sc (Computer Science) who are based in or willing to work from Pune. You should be keen to learn Stream Processing, Apache Kafka, Spark Streaming or Flink on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.

Perks

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursDirect access to the team that owns the data you work on

Interview & Selection Process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Team-fit / behavioural interview with the team
18,000/month

Stipend · 2 months

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Openings14 positions
Applicants0 applied
ModeHybrid
CategoryData Science
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