Job Description & Details
This is a hands-on data engineering gig where you will spend a good chunk of your time wrangling data, tuning SQL Server, and making sure pipelines don't silently fail in production. It is a classic data backend role where your primary stakeholders will be data scientists and business analysts who need reliable, clean datasets without the headache. If you like owning the data lifecycle from ingestion to modeling rather than just writing single queries, this one is worth a look.
What You'll Actually Be Doing
Expect to spend your days knee-deep in MS SQL Server, building and maintaining ETL pipelines, and figuring out why a specific data transformation job is dragging down database performance. You will be designing data models for the data science team, writing robust data quality checks, and acting as a part-time DBA when scheduling, error handling, or job monitoring goes sideways. Documentation and source-to-target mapping are also part of the deal, so keeping things clean and reproducible for the rest of the engineering organization is non-negotiable.
The Core Tech Stack
Your bread and butter here will be MS SQL Server and a solid suite of ETL and data integration tools. You need to know your way around Data Warehouses and Operational Data Stores (ODS) inside and out, plus have a strong grasp of data modeling and testing frameworks specifically for data transformations. If you have some background in Commercial Real Estate tech, you will instantly understand the context of the data models you are building, though solid core data engineering fundamentals will carry you through.
Interview Expectations
They are going to test your practical troubleshooting skills, likely asking you how you diagnose a failing production ETL job that is timing out on a massive table load. Be ready to explain your strategy for optimizing a sluggish SQL query and how you ensure data integrity during complex multi-source migrations. The hiring manager wants to see that you can think on your feet, handle unexpected database errors independently, and protect data quality without needing constant hand-holding.
Application Advice
Make sure your resume highlights your hands-on experience with MS SQL Server, ETL development, and data warehouse testing front and center. Use keywords straight from the description like 'data pipeline architecture', 'source-to-target documentation', and 'database performance' to get past the recruiter screens. If you have past contract work where you wore multiple hats as both a developer and a DBA, emphasize that versatility because this team explicitly needs someone who can jump into various parts of the data stack without breaking a sweat.