Sr. Data Engineer

One-day interview loop consisting of: * Python Coding Assessment

• Candidates must write code during the interview.
• Approximately 1.5 hours of total coding assessments.

• SQL Assessment

• Must be able to write and explain SQL solutions.

• System Design / Architecture Discussion

• Data engineering architecture and design-focused questions.

Suppliers are encouraged to conduct their own technical screening prior to submission, as the hiring team prefers candidates who have already been vetted. Additional Notes

• Work is primarily batch-processing focused.
• Databricks will be used heavily during discovery and proof-of-concept phases before production implementation.

Must-Have:

• Python
• Spark
• SQL
• Airflow
• AWS Glue
• Databricks

Preferred/Nice to Have:

• Delta Lake
• Snowflake
• API experience

Strong Differentiators:

• Data profiling and analysis
• Data mapping
• Production support experience
• Vulnerability remediation
• Experience supporting and maintaining pipelines in production environments

Candidate Profile

• Ideal experience level: 5-10 years, with 5-7 years being a strong target range.

• Candidates should demonstrate the ability to:

• Design and build data pipelines
• Support and troubleshoot production workloads
• Perform data analysis, profiling, and mapping
• Own operational support responsibilities in addition to development work

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