Intern - IT

Responsibilities

As part of the team, you will have opportunities to:

Work with data using Python and SQL to perform data preparation, analysis, transformation, and basic data quality checks.

Develop simple scripts, utilities, and automation solutions to improve repetitive or manual processes.

Learn and contribute to data pipelines and data engineering solutions using technologies such as Python, PySpark, Databricks, and cloud platforms.

Explore and build Generative AI prototypes using Large Language Models (LLMs), APIs, prompt engineering, and related technologies.

Experiment with AI-assisted solutions for information extraction, summarization, search, insights, and workflow automation.

Assist in developing and integrating APIs and software components.

Create simple reports, dashboards, or visualizations to communicate insights from data.

Perform testing, validation, debugging, and documentation of solutions.

Collaborate with team members to understand business problems and translate them into simple technical solutions.

Learn and follow good software development practices including Git, Agile, CI/CD, data governance, and responsible AI practices.

Skills & Qualifications

We are primarily looking for

strong fundamentals, curiosity, and willingness to learn

rather than extensive experience with specific technologies.

Essential

Bachelor’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, or a related field.

Good programming fundamentals, preferably using Python.

Basic understanding of SQL, databases, and working with data.

Understanding of core programming concepts, data structures, debugging, and problem solving.

Interest in Data Engineering, Automation, AI, and Generative AI.

Strong analytical and problem-solving mindset.

Good written and verbal communication skills.

Ability to learn new technologies and work collaboratively in a team environment.

Good to Have

Exposure through

academic projects, internships, certifications, hackathons, or personal projects

in one or more of the following areas would be an advantage:

Python libraries such as pandas or PySpark

Data platforms such as Databricks

Cloud platforms such as AWS, Azure, or GCP

Generative AI and LLMs, including OpenAI APIs, LangChain, LangGraph, or similar frameworks

Concepts such as prompt engineering, embeddings, RAG, or AI agents

Automation using Python, APIs, or workflow automation tools

REST APIs and basic web/service integration

Visualization tools such as Power BI or Tableau

Git/GitHub and basic CI/CD or DevOps concepts