Events & Community Growth Intern

Scope of the Role: 

We are looking for a curious and driven Data Engineering Intern to join our Data & AI team. You will primarily focus on building and maintaining robust data pipelines and infrastructure, while also contributing to applied AI projects involving Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.

This is a hands-on role. You will work alongside senior engineers and data scientists, contribute to production-grade systems.

The role is roughly 65% Data Engineering and 35% Data Science / Applied AI.

What You’ll Own:

Data Engineering

• Design, build, and maintain scalable ETL/ELT data pipelines using tools like Apache Airflow, dbt, or Spark
• Work with structured and unstructured data from various sources — APIs, databases, event streams
• Write optimized SQL queries and data transformation logic for analytical and ML use cases
• Maintain and improve data quality, schema management, and pipeline monitoring
• Collaborate on data warehouse and data lake architecture (e.g., Snowflake, BigQuery, Delta Lake)
• Document data flows, lineage, and schema definitions

Data Science & Applied AI

• Build and evaluate RAG pipelines — chunking, embedding, indexing, and retrieval
• Work with vector databases (e.g., Pinecone, Weaviate, pgvector) for semantic search
• Integrate LLM APIs (OpenAI, Anthropic, open-source models) into data products or internal tools
• Help with prompt engineering, evaluation frameworks, and fine-tuning experiments
• Support exploratory data analysis and feature engineering for ML workflows

You’ll Thrive in This Role If You Have:

• Pursuing a degree in Computer Science, Data Science, Engineering, or a related field
• Solid foundation in Python — comfortable writing clean, modular, production-quality code
• Hands-on experience with SQL (query optimization, CTEs, window functions)
• Familiarity with at least one cloud platform — AWS, GCP, or Azure
• Understanding of data pipeline concepts: batch vs streaming, orchestration, idempotency
• Strong analytical mindset with attention to data quality and correctness
• Experience with workflow orchestrators: Apache Airflow, Prefect, or Dagster
• Exposure to dbt for data transformation and testing

The expected hourly range for this position is $20/hour.

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