Director of Analytics Engineering
Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Oct 11, 2026.
Join Scribd, Inc., an AI-native company, as the Director of Analytics Engineering. In this role, you will lead a high-performing Analytics Engineering team, transforming fragmented data into trusted, reusable, production-quality data foundations. You will partner with Engineering to ensure critical data is captured, centralized, documented, secured, and governed. Your leadership philosophy will be grounded in service, and you will focus on building people and strengthening the discipline they share.
Missions
- Diriger et développer une équipe d'ingénierie analytique performante, en transformant des contributeurs individuels forts en une équipe cohésive et efficace.
- Établir un modèle opérationnel qui crée une structure sans bureaucratie inutile, en favorisant une culture et une communauté qui équilibrent les priorités locales avec le succès global de l'entreprise.
- Connecter les investissements en ingénierie analytique aux priorités de l'entreprise, en communiquant clairement les compromis aux dirigeants seniors.
Profil recherché
- Demonstrated ability to lead cross functional data initiatives from strategy through production adoption and measurable business impact- Excellent written and verbal communication with technical teams, business stakeholders, and senior executives
- Experience designing the data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems that ensure data and AI products are reliable, explainable, trustworthy, and safe to operate at scale
- 10+ years of experience in analytics engineering, data engineering, business intelligence engineering or a related discipline, including 5+ years leading and developing technical teams
- Proven track record of building, scaling, and leading high performing teams, turning strong individual contributors into cohesive and highly effective teams that are valued as strategic partners
- Depth in building governed, canonical data models and semantic layers, giving core business concepts one authoritative, discoverable definition instead of letting teams reconcile competing sources
- Strong judgment in balancing immediate stakeholder needs with long term investments in reusable data products, platform health, and technical debt reduction
- Advanced SQL skills and production experience with modern data stack, including AWS, Databricks, Airbyte, Fivetran, Looker, or comparable platforms
- Experience leading data cleanup efforts and implementing role based access controls and data retention policies to improve data quality, security, and governance
- Advanced Python
- Experience leading on call rotations, coordinating incident response, resolving production issues, and driving follow up improvements that strengthen system reliability
- Experience designing and building canonical data models and semantic layers that support financial analysis at scale