Job Description & Details
This is a heavy-hitting architecture role where you will be parachuting into legacy environments to drag their Hadoop monoliths kicking and screaming into Snowflake. If you enjoy untangling messy data spaghetti and architecting enterprise-grade cloud platforms for skeptical financial institutions, this gig will keep you on your toes.
What You'll Actually Be Doing
Expect to spend your days designing large-scale cloud data migrations, untangling legacy Hive queries, and convincing stakeholders that the cloud is actually secure. You'll be leading distributed engineering teams while wearing multiple hats: part strategic solution architect, part hands-on technical lead, and part diplomat managing client expectations in heavily regulated banking sectors.
The Core Tech Stack
You absolutely cannot fake your way through this without deep, battle-tested expertise in Snowflake and Hadoop ecosystems like Cloudera and Spark. Python and advanced SQL are your daily bread and butter for driving data transformations, alongside a firm grasp of data modeling, end-to-end orchestration, and meticulous data reconciliation protocols.
Interview Expectations
The hiring managers are going to probe deeply into your failure modes, specifically asking about how you handle data loss or drift during a massive Hadoop-to-Snowflake migration. They want to see that you can calmly walk through a disaster recovery scenario and articulate how you build CI/CD pipelines that actually work for data engineering rather than breaking every time a schema shifts.
Application Advice
Your resume needs to scream cloud migration and enterprise scale, so drop the fluff and highlight concrete metrics like terabytes migrated, downtime minimized, and distributed teams led. Make sure keywords like Snowpark, data lineage, Cloudera, and financial services compliance are front and center so you easily clear the ATS hurdle.