Data Engineer Intern

We're looking for a Data Engineer Intern to help design, build, and scale the data infrastructure that powers Referlly. You'll work on the plumbing that makes analytics and ML possible — ETL pipelines, data warehouse modelling, and data quality systems. If you love clean schemas, reliable pipelines, and knowing that your work unblocks an entire analytics team, this is for you.

What You'll Do

• Design and build robust ETL/ELT pipelines to ingest data from REST APIs, databases, and third-party tools
• Model and maintain data warehouse schemas (fact and dimension tables) optimised for analytics and reporting
• Optimise slow SQL queries and data storage layouts for cost and performance
• Set up monitoring, alerting, and data quality checks for pipeline health
• Define and enforce data contracts between upstream producers and downstream consumers
• Collaborate with data analysts to understand their query patterns and model data accordingly
• Explore real-time data streaming use cases using tools like Kafka or Pub/Sub where applicable
• Document pipelines, schemas, and data lineage to keep the warehouse maintainable

What We're Looking For

• Pursuing or recently completed a degree in Computer Science, Information Technology, or a related engineering field
• Solid understanding of SQL and relational databases — PostgreSQL or MySQL preferred
• Proficiency in Python; comfortable with libraries like Pandas, SQLAlchemy, or PySpark
• Familiarity with at least one cloud platform (AWS, GCP, or Azure) and services like S3, BigQuery, or Redshift
• Exposure to workflow orchestration tools (Airflow, Prefect, or Dagster) is a strong plus
• Understanding of data modelling concepts — star schema, normalisation, slowly changing dimensions
• Experience with version control (Git) and comfortable working in a code-review culture
• Curiosity about data quality and a habit of testing your own pipelines before shipping

What You'll Get

• Internship completion certificate and a detailed letter of recommendation
• Opportunity to convert to a full-time Data Engineer role based on performance
• Direct access to founders — weekly 1:1s and real strategic conversations
• Fully remote and flexible schedule — we care about outcomes, not hours
• Build production-grade data systems from scratch at an early-stage startup
• Own entire pipelines end-to-end — great for your portfolio and future interviews
• Exposure to the full modern data stack: ingestion, transformation, warehousing, and serving