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GIC Re logo — GIC Re Data Modelling Intern in Pune, Maharashtra
GIC Re VerifiedActively Hiring

Data Modelling Intern

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Location

Pune, Maharashtra

Work Mode

Hybrid

Duration

2 months

Stipend

₹25,000/mo

Start Date

Immediate / Rolling

Openings

11 positions

Type

Full-time

Category

Data Science

Apply Now — ₹25,000/moApply on Company Website ↗

About the Internship

Join GIC Re in Pune as a Data Modelling Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on dimensional and logical data modelling work. About the role As a Data Modelling Intern at GIC Re, your core…

About GIC Re

GIC Re offers a mentor-led Data Modelling Intern in Pune with live project work in data science, a stipend of ₹25,000/month and a Pre-Placement Offer opportunity for strong performers.
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Pune, MaharashtraVerified employer11 openings
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Skills Required

Dimensional ModellingStar & Snowflake SchemaNormalisationSQLER DiagramsSlowly Changing DimensionsData WarehousingRequirements GatheringDocumentationData Governance

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), BCA/MCA, B.Sc/M.Sc (Computer Science / Statistics) or MBA (Systems) who are based in or willing to work from Pune. You should be keen to learn Dimensional Modelling, Star & Snowflake Schema, Normalisation 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

Flexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorStructured onboarding and a formal mentor at a large, established employer

Interview & Selection Process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Discussion with the hiring manager on the role and your fit
25,000/month

Stipend · 2 months

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Openings11 positions
Applicants0 applied
ModeHybrid
CategoryData Science
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