Yes — but only if you learn the right things. The question is not really about experience; it is about what you can demonstrate in an interview.
A lot of freshers make the mistake of thinking they need to know every big data tool before applying for a junior role. In reality, most companies hiring freshers into data engineering are not expecting expertise in Kafka or Databricks. They want someone who understands data, can write good SQL, knows enough Python to automate a task, and has a basic grip on how data moves between systems.
What actually gets freshers shortlisted
The resumes that get callbacks tend to have a few things in common: real projects, clean SQL, and evidence that the person understands ETL — not just the acronym, but the actual process of extracting data from a source, cleaning it, and loading it somewhere useful.
Git, basic cloud familiarity (even free-tier AWS), and knowing how to write a Python script to pull from an API — these things signal that you can function on a real team. Certificates from video courses, by contrast, signal almost nothing on their own. They only matter if the work you did to earn them shows up in your projects.
The project problem
This is where most freshers fall short. They finish a course, add it to their resume, and then list the tools they "know" without showing what they built. Recruiters see this constantly and it does not move the needle.
What works better: a GitHub repo with a small but complete ETL pipeline that pulls real data from a public API, transforms it in Python, loads it into a database, and has a README that explains why you made the design choices you did. Even a modest project like that is more convincing than a long list of tools.
What to focus on as a fresher
Start with SQL until you are genuinely comfortable with joins, window functions, and CTEs. Then get Python to the point where you can write a script without looking everything up. After that, learn how to build a basic ETL pipeline — even using simple tools — and deploy something to AWS, even if it is just an S3 bucket and a Lambda function. That combination is enough to start applying.
At ShifttoTech Academy, the data engineering program is structured around exactly this progression. Students build ETL pipelines using real datasets, work with AWS services, and finish with portfolio projects they can walk through in an interview. The goal is not to teach tools in isolation — it is to give you something you can actually show.