Job Description & Details
This is a solid, heads-down data engineering gig centered around wrangling legacy and modern data sources into a centralized warehouse. If you enjoy tuning ETL pipelines, dealing with messy data migrations, and making SQL queries run faster, this 12-month contract will keep you legitimately busy without unnecessary startup chaos.
What You'll Actually Be Doing
You'll spend most of your time designing, building, and maintaining SSIS packages that pull data from various operational systems, transform it reliably, and load it into the data warehouse. Day-to-day work involves collaborating with business analysts to figure out why a particular data feed is failing, refactoring slow-running packages to handle growing data volumes, and ensuring your ETL architecture doesn't break when upstream schemas inevitably change.
The Core Tech Stack
You need absolute fluency in SQL Server Integration Services (SSIS) and deep expertise in T-SQL. The team relies heavily on SQL Server databases, so you must know your way around indexing strategies, execution plans, and query optimization. A solid grasp of dimensional data warehousing concepts is non-negotiable here, because you won't just be moving data blindly—you'll need to structure it properly for downstream reporting.
Interview Expectations
Expect the hiring manager to ask you to walk through a time you troubleshot a severely performing SSIS package, specifically how you identified whether the bottleneck was in the data flow, network, or the destination database. They are looking for methodical debugging skills rather than textbook answers. You'll also likely be grilled on how you handle incremental loads versus full refreshes, so be ready to discuss your strategy for handling delta data changes efficiently.
Application Advice
Skip the generic objectives on your resume and make sure your experience explicitly highlights large-scale ETL implementations and T-SQL performance tuning. Mirror the exact terminology from the job description—terms like "SSIS packages," "data warehousing concepts," and "ETL processes" need to be front and center so your resume easily clears their automated screening filters.