Job Description & Details
This is a solid entry-level gig if you are trying to break into the data space without getting bogged down by unrealistic senior requirements. You will spend your days doing the foundational blocking and tackling of data work—cleaning messy datasets, supporting ETL pipelines, and helping build out basic dashboards.
What You'll Actually Be Doing
You will be rolling up your sleeves to assist the senior engineering team with data ingestion, transformation, and quality checks. Expect to write plenty of SQL queries to extract data, troubleshoot broken pipelines, and help translate raw tables into clean, usable reporting assets. It is a grind, but it is the exact kind of hands-on repetition needed to level up your technical baseline quickly.
The Core Tech Stack
You need a functional understanding of SQL and relational databases because you will be querying data daily. Python is your go-to scripting language for data manipulation, and knowing your way around Excel is still non-negotiable for quick ad-hoc analysis. If you have touched Power BI, Tableau, or any cloud platform like AWS or GCP, highlight that immediately—it is what separates a resume from the trash pile here.
Interview Expectations
Expect the hiring team to test your SQL chops with some basic JOINs, group-by aggregations, and subqueries to see how you think through data manipulation. They are also going to ask you to walk through a personal project or internship where you had to clean a messy dataset, looking specifically for how you handle missing values and logic errors under pressure.
Application Advice
Do not just list every tool you have ever heard of on your resume; explicitly show how you used SQL and Python in an academic project, certification lab, or internship. Make sure terms like ETL, data cleaning, and database operations are front and center so you easily clear the initial ATS keyword sweep.