Location
Coimbatore, Tamil Nadu
Work Mode
Hybrid
Duration
6 months
Stipend
₹24,000/mo
Start Date
Immediate / Rolling
Openings
13 positions
Type
Full-time
Category
Data Science
About the Internship
Join McKinsey & Company in Coimbatore as a Data Integration Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on data governance and data quality work.
About the role
As a Data Integration Intern at…
About McKinsey & Company
McKinsey & Company offers a mentor-led Data Integration Intern in Coimbatore with live project work in data science, a stipend of ₹24,000/month and a Pre-Placement Offer opportunity for strong performers.
See all McKinsey & Companyinternships →Coimbatore, Tamil NaduVerified employer13 openings
Apply to McKinsey & Company →Skills Required
Data GovernanceData QualitySQLData CataloguingMaster Data ManagementData LineageExcelValidation RulesStakeholder AlignmentDocumentation
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech (any branch), BCA/MCA, B.Sc (Statistics/Mathematics), B.Com/BBA or MBA who are based in or willing to work from Coimbatore. You should be keen to learn Data Governance, Data Quality, SQL 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 hoursStructured onboarding and a formal mentor at a large, established employer
Interview & Selection Process
4 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Discussion with the hiring manager on the role and your fit
- 3Team-fit / behavioural interview with the team
- 4HR discussion — stipend, start date, expectations and offer
₹24,000/month
Stipend · 6 months
Openings13 positions
Applicants0 applied
ModeHybrid
CategoryData Science
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