Job Description & Details
This is a hands-on, 12-month contract role sitting in Alpharetta where you'll spend your days wrangling data, evaluating sources through the classic 5Vs, and writing heavy Python and SQL scripts. It's a structured environment where documentation and SDLC adherence matter just as much as the code you push.
What You'll Actually Be Doing
You'll be bridging the gap between raw data and business metrics by collaborating closely with data SMEs and owners to figure out what data is actually available and whether it's trustworthy. Your day-to-day will involve writing Python scripts to extract and transform messy datasets, partnering with database teams to onboard new sources, and guiding visualization teams on how to build metrics correctly. Expect to spend a decent amount of time creating process documentation and validating data integrity to make sure it holds up to rigorous tech controls and risks.
The Core Tech Stack
Python is your bread and butter here—specifically Pandas, NumPy, RegEx, and Lambda functions—alongside strong SQL skills to dig into databases. You'll also need solid intermediate Excel chops for quick data checks, plus modern tooling experience like GitHub and AI assistants like Claude or Copilot to speed up your validation workflows. If you know Snowflake and DevOps concepts, you'll have a major leg up in hitting the ground running.
Interview Expectations
Since this is an in-person interview process requiring strong Python and SQL chops, expect them to test your data manipulation intuition under pressure. They might ask you to explain how you'd optimize a sluggish Pandas dataframe operation or write a complex SQL query involving window functions to handle missing or dirty data. The hiring manager is secretly looking for someone who doesn't just write code that works, but someone who understands data quality verification and can articulate why a dataset is or isn't fit for critical business metrics.
Application Advice
To get past the ATS and grab the recruiter's attention, make sure your resume explicitly highlights your hands-on experience with Pandas, NumPy, and advanced SQL querying rather than just listing them as buzzwords. Emphasize your project management background and any specific instances where you documented data pipelines or collaborated with cross-functional database teams. Finally, explicitly mention your familiarity with AI coding assistants and GitHub workflow management to signal that you work efficiently in modern tech environments.