Intern Data Engineer

Internship details:

• The internship will begin January 11th 2027

• 20-25 hours/week work dedication during the semester and up to 40/week during breaks

• Anticipated graduation date between May 2027 - December 2027

Position Highlights

We areseekinga curious motivated Data Engineer Intern to support the design development and optimization of modern data platforms that power analytics experimentation and emerging AI-driven workflows. This internship provides hands-on exposure to cloud data ecosystems such as Databricks Snowflake AWS Azure and GCP with opportunities to contribute to real-world ETL/ELT pipelines data transformations and AI agentenabled use cases.

As an intern you will work closely with experienced data engineers analytics teams and AI practitioners to learn how reliable data foundations enable intelligent agents automation and data-driven decision-makingwhile gaining practical experience in scalable privacy-aware data engineering.

Key Responsibilities

• Assistin building andmaintainingbatch and streaming data pipelines using tools such as Spark Databricks Snowflake and cloud-native services.

• Support the development of ETL/ELT workflows using orchestration tools like Apache Airflowdbt or managed cloud schedulers.

• Help ingest structured and semi-structured data from sources such as S3 ADLS GCS APIs or Kafka into raw and curated data layers.

• Write andmaintainSQL and Python-based transformations for cleaning joining and aggregating datasets.

• Participate in implementing data quality checks validation rules and basic monitoring to ensure data accuracy and reliability.

• Collaborate with data engineers analysts and data scientists to understand how datasets are consumed by analytics models and AI agents.

• Assistin preparing datasets and feature tables that can be used by AI/ML pipelines or autonomous agents for decision-making and automation.

• Explore how AI agents can interact with data platforms (e.g. querying data triggering pipelines summarizing results) under guidance from senior team members.

• Contribute to documentation of data flows schemas and pipeline logic to support team knowledge sharing.

• Learn and follow data modeling governance and privacy best practices especially in regulated or privacy-conscious environments.

• Support version control and deployment processes using Git and basic CI/CD workflows.

Required Qualifications

• Currentlypursuing a Bachelors orMasters degree in Computer Science Data Science Engineering Information Systems or a related field.

• Basicproficiencyin SQL including simple joins aggregations and filtering.

• Familiarity with Python for scripting data manipulation or coursework projects.

• Introductory understanding of data engineering concepts such as ETL/ELT data lakes and data warehouses.

• Exposure to at least one cloud platform (AWS Azure or GCP) through coursework labs or personal projects.

• Interest in AI machine learning or intelligent systems especially how they depend on high-quality data.

• Strong willingness to learn ask questions and collaborate in a team environment.

• Clear written and verbal communication skills with attention to detail.

Preferred Qualifications

• Academic or personal project experience with Databricks Snowflake toApache Sparkdbt or workflow orchestration tools.

• Familiarity with common data formats such as Parquet JSON Avro or Delta Lake. Basic understanding of streaming vs. batch processing concepts.

• Coursework or projects involving AI agents LLMs or ML pipelines such as:

• Using agents to query data or generate insights

• Automating data-related tasks with AI-assisted workflows

• Awareness of data privacy concepts (e.g. PII GDPR CCPA) even at a conceptual level.

• Experience working in GitHub or similar version control systems.