Back
Senior, specialized data-platform role with reputable employer increases applicant competition.
Data-platform skills are transferable, but semantic-layer and dbt/Snowflake specialization raises domain specificity.
Explicit 8+ years, 2+ years management, and required dbt/Snowflake/semantic-layer expertise.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead and grow a team of 5+ data engineers responsible for building and maintaining the enterprise data platform infrastructure.
Drive architectural decisions focusing on Data Sharing and Semantic Layer design ensuring high availability, scalability, and security.
Own platform operational health including monitoring, incident response, and performance optimization aligned with the data platform roadmap.
8+ years in data or software engineering with at least 2 years managing engineering teams of 5 or more.
Expertise in designing complex data architectures, specifically Semantic Layering and Data Sharing at enterprise scale.
Hands-on experience with dbt, semantic models (e.g., MetricFlow), Snowflake, and SQL; familiarity with Spark, Python, Snowpark is a plus.
Experience managing on-call processes, incident management, operational metrics, CI/CD practices, and data observability tools.
Experienced engineering manager capable of balancing technical leadership with people management in data infrastructure contexts.
Strong strategic execution ability translating business requirements into technical priorities and influencing cross-functional stakeholders.
Background in modern data platform technologies and operational rigor driving platform reliability and engineering standards.