Lead Data Engineer

What you'll do

• Identify and map current-state data sources, ownership, and quality gaps within infrastructure product teams.
• Design and deliver integrations to publish governed data products into a data mesh ecosystem.
• Establish data quality rules and monitoring at the source to drive root-cause remediation.
• Standardize critical data attributes and definitions across domains for reliable downstream consumption.
• Define and implement data contracts to manage producer/consumer expectations and reduce operational risk.
• Reconcile and certify infrastructure asset inventories to eliminate security and control gaps.
• Maintain metadata management practices including cataloging, lineage, and stewardship signals for auditability.

What we're looking for

• Formal training or certification in data engineering concepts and 5+ years of applied experience.
• 5+ years of hands-on data engineering experience in data modeling, pipeline development, and quality engineering.
• Proficiency in Python and SQL to build reliable, testable data transformations and integrations.
• Demonstrated experience diagnosing data quality issues and implementing controls to prevent recurrence.
• Working knowledge of infrastructure or asset-related data domains sufficient to model and normalize inventory data.
• Experience working directly with partner teams and ability to lead efforts through ambiguity.
• Familiarity with data contract patterns and practical data quality frameworks (preferred).
• Experience with IT asset management, data mesh models, graph databases, or streaming services like Kafka (preferred).