Responsibilities:

Lead the evaluation of senior data engineering and architecture talent by conducting structured, scenario-driven interviews that measure real-world problem-solving ability.
Assess technical depth across distributed data processing, cloud-scale data platforms, and modern lakehouse technologies, with a focus on practical application rather than memorized responses.
Develop and apply consistent interview frameworks that allow fair comparison across candidates while maintaining strong time management throughout the process.
Probe candidates on how they would investigate data pipeline failures, performance issues, and data integrity concerns within large-scale Spark and Databricks environments.
Review whether candidates can translate ambiguous business objectives into clear source-to-target mappings and implementation-ready data requirements.
Evaluate data quality, governance, lineage, and metadata management knowledge to ensure alignment with enterprise data standards.
Partner with hiring stakeholders to identify candidates who can clearly explain technical concepts to non-technical audiences and work effectively across functional teams.
Provide informed feedback on candidates' strengths in Python, SQL, data lake architecture, and scalable analytics solution design.
Support assessment activities related to governance approaches such as federated or data-mesh models, particularly in regulated or compliance-focused settings.

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