Data integration Intern

Honeycomb is a division of American Iron & Metal (AIM), a family-owned company and recognized global leader in the metal recycling industry with more than 125 sites and 4000 employees worldwide. We have continued to prosper for the last eight decades thanks to the dedication of our employees and the ongoing trust and support of our customers. 

Honeycomb purchases and processes catalytic converters to recover and refine PGMs (platinum group metals).

Why? To give a converters a second life and to strive to reduce the environmental impact associated with metal extraction. We work hard to keep our partners happy, and our business clean.

The Data Integration Intern will play a key role in developing scalable and automated data‑processing workflows to support ongoing data science initiatives. This role involves building ingestion pipelines in Azure Databricks, creating Python and PySpark‑based data‑cleaning and validation workflows, and implementing corporate standards to ensure full traceability, clear data lineage, and reproducible processes.

What you’re responsible for:

• Developing automated data cleaning and validation workflows using Python and PySpark notebooks, along with Databricks pipelines, to support a data science project.
• Building robust ingestion pipelines in Databricks to efficiently load, process, and prepare data for downstream analytics and modeling.
• Ensuring full traceability of data cleaning methodologies by designing workflows that follow the Medallion Architecture (Bronze → Silver → Gold), maintaining clear lineage and reproducibility.
• Implementing corporate standards for data‑cleaning notebooks to improve readability, consistency, maintainability, and ease of handoff across teams.
• Developing reusable, well‑documented functions (when necessary) that are readable, modular, and include strong error‑handling measures to support scalable and reliable data processing.

Qualifications To join our team

• Bachelor’s or Master’s degree in Computer Science, Data Science, Data Engineering, or a related field.
• 1–2 years of experience in a similar corporate or professional environment.
• 1 year of experience building ingestion pipelines using PySpark and Azure Databricks is considered a strong asset.
• Hands‑on experience working on data science projects within a corporate setting, including exposure to model‑ready data preparation and validation workflows.
• Proficiency in Python, including experience with Jupyter notebooks, Azure Data Warehouse, and Databricks/Fabric/PySpark notebooks.
• Experience contributing to exploratory data analysis (EDA) and strategic data cleaning for data science initiatives is considered a strong asset.

The advantages (!):

• Eligible for paid vacation from the first day;
• Comprehensive group insurance plan;
• Telemedicine (Unlimited access to a doctor 24/7);
• Group RRSP with employer matching contributions;
• AIM tuition assistance grants;
• Referral program;
• Exclusive employee discounts on parts at any Honeycomb location;
• Company-organized events throughout the year (barbecue, Christmas party, etc.);
• Exceptional advancement opportunities.