Job Description & Details
This 12-month contract role drops you right into an enterprise Information Security data warehouse team where your primary job is to wrangle, clean, and pipe complex security data into usable formats. If you enjoy deep data dives and building reliable reporting pipelines rather than just pushing tickets, this gig offers a solid runway to make an impact.
What You'll Actually Be Doing
You will spend your days wrist-deep in data curation, transformation, and validation, figuring out why upstream security feeds are breaking and writing automation scripts to keep things running smoothly. Expect to spend a significant amount of time translating vague business requirements from security stakeholders into concrete data solutions, writing bulletproof SQL queries, and building out BI dashboards that actually tell a story without cluttering the screen.
The Core Tech Stack
Your bread and butter here will be advanced MS SQL and Python, so you need to be comfortable optimizing gnarly queries, writing stored procedures, and spinning up Python scripts for data processing and integration across disparate sources. Experience with BI tools like Qlik, Power BI, or Tableau is a must since you'll be delivering the final reporting products, while bonus points go to anyone who has touched Starburst/Trino or dabbled in security data domains.
Interview Expectations
Be prepared for a deep dive into your SQL optimization techniques, where they might ask you how you would troubleshoot a stored procedure that's timing out on a multi-million row security log table; the hiring manager is secretly testing whether you understand indexing and execution plans or if you just write queries that happen to work. You should also expect a live Python scenario testing your data manipulation logic, where they want to see clean, readable code and hear how you handle edge cases like missing or corrupted data streams.
Application Advice
Make sure your resume doesn't just list SQL and Python, but explicitly highlights the scale of the data pipelines you've built and the business impact of your dashboards. Mirror the exact terminology from the job description regarding 'data curation,' 'quality validation,' and 'process automation' so you easily sail past the ATS filters before a human ever looks at your profile.