Stoxkart

Data Engineer Intern

InternshipWork from HomeKannur, Kerala6 months35K/mo3 openingsImmediate / Rolling

About this internship

Start your career in data engineering and large-scale pipelines with Stoxkart as a Data Engineer Intern in Kannur. You will sit with a working team, use the same tools and systems they do, and own a defined piece of work from day one. About the role As a Data Engineer Intern at Stoxkart, your core…

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Skills you'll use

PySparkDatabricksSnowflakeApache KafkaETL Pipeline DevelopmentAdvanced SQLApache AirflowData Modelling & WarehousingPythonCloud Storage (S3 / ADLS / GCS)

What you'll do

Work on building and hardening the ETL pipelines the rest of the company reports on alongside the core team
Apply PySpark, Databricks, Snowflake, Apache Kafka to live, production-facing problems
Document your work clearly for reviewers and stakeholders
Participate in reviews and act on the feedback you receive
Collaborate across engineering, product, design or business as required
Follow the team's quality, testing and documentation standards

Who can apply

Pursuing or recently completed B.E./B.Tech (CSE/IT), BCA, MCA or M.Sc (Computer Science) — 2026 freshers & final-year students welcome
Working knowledge of PySpark, Databricks, Snowflake (or a genuine willingness to learn them)
Strong fundamentals in your discipline and clear problem-solving ability
Care with detail and the discipline to document your work
Clear written and verbal communication in English
Based in or willing to work from Kannur, Kerala

Perks & benefits

Letter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunity

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Technical interview on fundamentals and your projects

About Stoxkart

Stoxkart operates in the stock broking sector and has an active presence in Kannur. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a distance. The work…

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