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Data Engineering Intern Jobs in Ontario (NOW HIRING)

Intern Orientation * Online Onboarding Curriculum * Buddy Program for mentorship and guidance Hands ... Data Modeling & Engineering: Build and maintain robust semantic models for both BI and AI ...

$23.75 - $29.75/hr

Engineering analysis and drafting assistance Surveying and Engineering Technology * Field data collection and mapping * Utility and infrastructure documentation * GIS data management and analysis

About Marvell Marvell's semiconductor solutions are the essential building blocks of the data ... Currently pursuing a Master's or PhD in Electrical Engineering or a related field. * Coursework or ...

AI Engineer Intern

Toronto, ON · Hybrid

CA$20 - CA$30/hr

We are looking for an AI Engineer Intern interested in building production-ready AI agents and ... Data Science, Software Engineering, or a related field. * Strong programming skills in Python.

Design, implement and validate components, weldments, assemblies, and integrations for engineering ... data. Permanent Full time employees may also be eligible for our comprehensive benefits package ...

Design, implement and validate components, weldments, assemblies, and integrations for engineering ... data. Permanent Full time employees may also be eligible for our comprehensive benefits package ...

Your Team, Your Impact Central Engineering works directly with the Optical Digital Signal Processing (ODSP) group to design physical layer ICs for high-speed fiber optic data communication, such as ...

Showing results 41-60

Data Engineering Intern information

What does a data engineering intern do?

A Data Engineering Intern assists in building and maintaining the systems and infrastructure that allow organizations to collect, store, and analyze large volumes of data. Their responsibilities often include cleaning and organizing raw data, developing data pipelines, and supporting the work of data engineers and data scientists. Interns may also work with tools like SQL, Python, and cloud platforms to automate data workflows. This role provides hands-on experience in managing data processes and understanding the fundamentals of data engineering in a real-world environment.

What types of projects and technologies can a data engineering intern expect to work with during their internship?

As a Data Engineering Intern, you’ll typically work on projects involving data pipeline development, data cleaning, and integration of data from various sources. You can expect to use technologies like SQL, Python, and tools such as Apache Spark, Hadoop, or cloud platforms like AWS or Google Cloud. Interns often collaborate closely with data engineers, analysts, and sometimes data scientists to ensure data is accessible, reliable, and well-organized for analysis. This hands-on experience helps you build foundational skills and understand real-world data workflows within a collaborative team environment.

What are the key skills and qualifications needed to thrive as a data engineering intern, and why are they important?

To thrive as a Data Engineering Intern, you need foundational knowledge in programming (especially Python or Java), databases, and data structures, often obtained through coursework in computer science or related fields. Familiarity with SQL, cloud platforms (like AWS or Azure), and data pipeline tools such as Apache Spark or Airflow is typically required. Strong problem-solving skills, attention to detail, and effective communication set exceptional interns apart. These skills and qualities are crucial for efficiently handling data workflows, collaborating with teams, and contributing to high-quality data solutions.

What is the difference between Data Engineering Intern vs Data Analyst Intern?

AspectData Engineering InternData Analyst Intern
Required SkillsBasic SQL, programming (Python, Java), understanding of data pipelinesData visualization, SQL, statistical analysis
Work EnvironmentData engineering teams, cloud platforms, data warehousesBusiness intelligence teams, reporting tools, dashboards
Industry UsageTech, finance, healthcare, any data-driven industryMarketing, finance, retail, business sectors

While both roles involve working with data, a Data Engineering Intern focuses on building and maintaining data pipelines and infrastructure, whereas a Data Analyst Intern analyzes data to generate insights and reports. The roles share some technical skills like SQL but differ in their core responsibilities and work environments.

What are the most commonly searched types of Data Engineering jobs in Ontario?

The most popular types of Data Engineering jobs in Ontario are:

What cities in Ontario are hiring for Data Engineering Intern jobs?

Cities in Ontario with the most Data Engineering Intern job openings:

Infographic showing various Data Engineering Intern job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Research Engineer - Post-training (Co-op / Intern)

Themis Intelligence

Mississauga, ON • Hybrid

CA$20 - CA$30/hr

Full-time, Internship

Re-posted 16 days ago


Job description

About Themis Intelligence Themis Intelligence builds the Utility Knowledge Base (UKB) and Human-Guided Intelligence (HGI) platforms, redefining how utilities operate. Our systems transform complex operational data into clear, high-confidence decisions. We design software that empowers grid professionals to think faster, act decisively, and operate with precision in critical environments. Every product we ship is built for real-world performance: reliable, observable, and secure from day one. We are an AI-first organization, continuously applying modern tools and workflows to improve how we plan, execute, and deliver outcomes. ------------------------------- About the Role We’re looking for a co-op student for a 12-month duration who’s curious about how LLM agents behave in real-world applications—especially when it comes to hallucination, grounding, and evaluation. You’ll be working on the post-training lifecycle of Themis Agents (e.g., knowledge base assistants, alarm summarizers, and SCADA-aware chatbots), ensuring that models are not only powerful but also accurate and trustworthy. You’ll contribute to designing and running evaluation frameworks, comparing retrieval strategies, testing prompt chains, and analyzing model behavior across a range of tasks. This is a hands-on, research-oriented role ideal for someone with AI-related coursework and a passion for building better, safer AI systems. ------------------------------- In this role, you will Evaluation & Grounding   §   Evaluate Themis Agents for accuracy, factual consistency, hallucination, and tool correctness.   §   Analyze grounding failures—when models “go off-script” from retrieved knowledge or internal documents.   §   Score and compare outputs across tasks like Q&A, summarization, and event reasoning. Prompt & Retrieval Testing * Experiment with prompt templates, few-shot examples, and retrieval settings. * Compare vector store search performance using embedding models, chunking strategies, and context window variations. * Run A/B tests across model versions and prompt chains. Tooling & Automation * Build or extend evaluation pipelines in Python and frameworks like LangChain, OpenAI API, or Transformers. * Visualize and organize test results using tools like Streamlit, pandas, or Dash. * Help define “hallucination types” and build reproducible test suites for failure tracking. ------------------------------- You might thrive in this role if you * Are pursuing a Bachelor’s degree in Computer Science, Engineering, Math, Physics, or a related field. * Have completed coursework in machine learning, natural language processing, or AI systems. * Enjoy debugging model outputs and understanding why a chatbot gave a weird answer. * Have worked on side projects involving chatbots, retrieval-based systems, or LLMs. * Can write clean Python code and think critically about accuracy, context, and grounding. ------------------------------- Bonus Points For * Experience with LangChain, LlamaIndex, or RAG architectures. * Familiarity with evaluation frameworks like lm-eval-harness, RAGAS, or custom harnesses. * Knowledge of vector databases (e.g., Qdrant) and prompt engineering techniques. * Interest in safety, reliability, or interpretability of AI agents.   This is a 12-month duration COOP/ Intern hybrid role (four days in-office) reporting directly to the Technology Director. The salary range for this role is $20–$30 per hours. Interested candidates are invited to submit their cover letter and resume.   Themis Intelligence values a diverse workplace and strongly encourages women, people of all races, color, creed, ancestry, ethnic origin, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, marital status, family status, and those with disabilities to apply.  We use AI tools to help streamline parts of our recruitment process, but every application is reviewed by a member of our team. Themis is an equal opportunity employer. We are committed to providing accommodations for persons with disabilities. If you require accommodation, we will work with you to meet your needs. While we appreciate the interest of all applicants, only those selected for an interview will be contacted.