Job Description & Details
This is a heavy-hitting data engineering role where you will be knee-deep in building integrations, wrangling Snowflake loads, and keeping complex reporting pipelines afloat. If you enjoy jumping into the weeds of SQL optimization and bridging the gap between legacy tools like SSRS and modern cloud data warehouses, this gig will keep you on your toes.
What You'll Actually Be Doing
You will spend your days writing complex SQL scripts, spinning up data integration feeds, and building automation workflows that directly feed the business. Expect to juggle migrating data into Snowflake while keeping legacy SSRS and Tableau reports happy. You will also be embedded in Agile ceremonies like daily stand-ups and backlog grooming, collaborating with both technical teammates and project sponsors to push automation projects through strict peer review and change management gates.
The Core Tech Stack
You need absolute mastery over SQL Development, Snowflake, and ETL tools like SSIS, alongside reporting powerhouses like SSRS and Tableau. Because this role touches automation and version control, having a solid grasp of PowerShell and GitHub is non-negotiable. Financial accounting and trading technology background is also a major plus here, as the data context heavily leans into high-stakes financial operations.
Interview Expectations
Expect the hiring team to grill you on your Snowflake optimization strategies, specifically asking how you handle massive data loads and performance tuning for complex SQL queries. The interviewer is secretly looking to see if you can debug under pressure and whether you understand the architectural tradeoffs of moving legacy SSRS environments into modern cloud ecosystems.
Application Advice
Your resume needs to scream heavy-duty data integration and Snowflake experience right at the top. Make sure to explicitly include keywords like SQL Development, Data Integration, SSRS Reporting, Snowflake, and Tableau to clear the ATS. Instead of just listing technologies, highlight specific instances where you successfully managed end-to-end data loads and guided automation workflows through strict change management procedures.