Job Description & Details
This is a heavy-duty data engineering and migration role where you will be knee-deep in modernizing large-scale systems for an enterprise tech environment. If you enjoy untangling legacy codebases, architecting robust data pipelines, and ensuring data integrity across complex distributed systems, this gig in Redmond is worth a serious look.
What You'll Actually Be Doing
Your day-to-day will revolve around building, testing, and fine-tuning data migration packages and custom software solutions. You'll spend a good chunk of time analyzing complex system requirements, writing code to migrate massive datasets, and performing rigorous unit testing to catch bugs before they hit production. Expect to troubleshoot unexpected data discrepancies, work closely with existing legacy systems, and ensure that post-implementation validation goes off without a hitch.
The Core Tech Stack
You absolutely need to be fluent in Python, SQL, and Apache Spark to survive and thrive here. The team relies heavily on these tools to process large volumes of data and execute complex data transformations. A rock-solid understanding of fundamental computer science concepts like data structures and algorithms is non-negotiable because you'll be optimizing performance bottlenecks in large-scale systems.
Interview Expectations
Be ready for deep-dive technical questions regarding distributed data processing, such as optimizing a slow-running Spark job by managing sharding and memory allocations. The interviewer is secretly testing whether you understand what happens under the hood of your code, not just whether you can write syntax that works. You'll also likely face a live coding challenge focused on data manipulation and algorithmic efficiency in Python or SQL.
Application Advice
Your resume needs to aggressively highlight your hands-on experience with Python, Spark, and SQL in the context of data migration or large-system engineering. Don't just list your past job titles; use specific keywords from the description like 'data quality checks,' 'unit testing,' and 'legacy systems integration' to ensure you sail past the ATS and grab the hiring manager's attention.