Introduction to Data Engineering

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This class will be live online (i.e. synchronous).

This course is a part of ProTech. Please review eligibility requirements below before applying.

Organizations can collect large volumes of information to make data-driven decisions but how do they make raw data usable and accessible at scale?

Data Engineering roles have grown in number and importance as organizations work to turn the information they already possess into something actionable by data scientists, analysts, and business teams. The increasing use of AI technologies has also created a need for well organized, clean, and well documented data sources.

This continuing education course introduces the fundamental concepts and hands-on skills behind modern data engineering: ingesting, storing, transforming, and serving data. You’ll learn the strategic differences between ETL and ELT, work with structured, semi-structured, and unstructured data, and build practical experience with industry-leading tools including DuckDB, Prefect, Databricks, Metabase, dbt and AWS.

This continuing education course is an abbreviated version of the Data Engineering Bootcamp we launched in 2025. It provides an introduction to the field of data engineering for software developers and data analysts.

Is this course for you?

  • Are you a Software Developer interested in building the pipelines and infrastructure that collect, store, and make large volumes of data usable?
  • Are you a Data Analyst or Scientist who wants to move beyond extracting insights to designing and building the systems that generate them?
  • Do you have a programming background with experience/familiarity with SQL and structured or semistructured data or databases and an interest in creating well-organized, reliable systems for collecting, managing, and storing data?

What will the course cover?

  • Data Engineering Fundamentals
    Get oriented in the data engineering landscape and understand what data engineers do and how ingestion, storage, transformation, and serving fit together in a modern data stack, including AI technologies.
  • ETL vs. ELT
    Learn the difference between Extract-Transform-Load and Extract-Load-Transform and develop the judgment to know which approach fits a given situation.
  • Data Structures
    Work with the three main types of data: structured (tables/rows), semi-structured (JSON), and unstructured (free-form text, files), and understand how each is handled differently in pipelines.
  • Cloud & Storage
    Get hands-on with AWS using the CLI, SSO profiles, and the boto3 Python library to interact with S3, Amazon's widely-used cloud object storage service.
  • DuckDB
    Use DuckDB, a fast in-process analytical database, for local data processing and you will be introduced to Polars, a modern DataFrame library built for performance.
  • Transformation
    Learn how dbt (data build tool) transforms raw data into clean, reliable datasets.
  • Orchestration
    Use Prefect to schedule and manage data workflows using flows, tasks, the local UI, and deploying pipelines with flow.serve().
  • Metabase
    Connect your data to Metabase to build visualizations and dashboards that make your data accessible to non-technical stakeholders.
  • APIs
    Pull data from external APIs using httpx and authenticate requests, handle paginated responses, and gracefully manage rate limits.
  • SQL & Data Transformation
    Advance your SQL skills with Common Table Expressions (CTEs) and learn data modeling concepts that underpin how analytical databases are structured.
  • Software Engineering Practices
    You will apply professional development standards including version control with Git, code quality, and documentation so your work is maintainable and team-ready.

How will you learn the material?

Hands-on Learning
Students actively engage in hands-on exercises and projects as opposed to being passively lectured to. Students leave with a deeper understanding of the subject matter and are ready to apply their new skills on the job.
Live Online Learning
Students have the opportunity to interact as a class, in smaller working groups and one-on-one with the instructor in a live virtual classroom.
Independent Learning
Self study exercises to prepare for class on your own time. Students should expect approximately 3-5 hours of independent study per week.

  • Schedule

    Mondays and Wednesdays 5:30 - 7:30 PM CT

  • Location

    This class is live online (i.e. synchronous).

  • Dates

    TBA

  • Tuition

    FREE

    This course is a part of ProTech. Please review eligibility requirements below before applying.
What is required?
  • Personal Computer with webcam and microphone
  • Must be 18+ years old
  • Experience with SQL, Python or other programming language, experience working with structured or semistructured data or databases
ProTech Eligibility
  • Must reside in Middle Tennessee
  • Graduate of NSS, another coding bootcamp, or college/university with tech-related degree AND searching for your first job in tech.
  • Tech professional who is unemployed after being laid off from a tech job

Attendance Information

Our policy regarding absences is based on making sure you get the most out of your professional development. Attendance is tracked for this course. Excused absences should be arranged with your instructor before they occur. Due to the short duration of this course we recommend that you not miss multiple days of this course. Absence due to emergencies are always excused as long as the instructor is notified as soon as possible.

Have questions?
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