5 дней назад
Director, Analytics Engineering (AI)
202 500 - 268 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Director, Analytics Engineering (AI): Building and scaling an Analytics Engineering organization and trusted data foundations for an AI-native Scribd, with an accent on governed canonical models, semantic layers, data quality, observability, and technical leadership. Focus on developing high-performing teams, guiding architecture and governance decisions, and turning data and AI investments into reliable production systems and measurable business impact.
Location: Hybrid work with occasional in-person attendance required. Primary residence must be in or near an approved city in the United States, Canada, or Mexico.
Salary: $202,500–$268,000 annually in California; $191,500–$254,000 annually in the United States outside California; CAD 177,000–235,000 annually in Canada. The position is also eligible for equity and benefits.
Company
advances human understanding through , Slideshare, Everand, and Fable.
What you will do
- Build, scale, and lead a high-performing Analytics Engineering team.
- Establish an operating model, team culture, career pathways, and distributed ownership.
- Guide technical decisions across data modeling, architecture, governance, quality, tooling, and developer experience.
- Build canonical datasets, shared metrics, semantic layers, and trusted production-quality data foundations.
- Lead cross-functional data initiatives from strategy through production adoption and measurable business impact.
- Apply AI-assisted development, analysis, agents, and automated workflows where they create clear value.
Requirements
- 10+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a related discipline.
- 5+ years leading and developing technical teams.
- Experience building and scaling high-performing teams and turning individual contributors into cohesive strategic partners.
- Deep experience with governed canonical data models, semantic layers, data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems.
- Advanced SQL and production experience with modern data platforms such as AWS, Databricks, Airbyte, Fivetran, or Looker.
- Excellent communication with technical teams, business stakeholders, and senior executives.
Nice to have
- Advanced Python.
- Experience with data cleanup, role-based access controls, and data retention policies.
- Experience building canonical data models and semantic layers for financial analysis.
- Experience leading on-call rotations, incident response, production issue resolution, and reliability improvements.
Culture & Benefits
- Flexible work model balanced with intentional in-person collaboration.
- Health, dental, vision, mental health, and disability coverage.
- Paid vacation, sick time, holidays, winter break, volunteer time, and sabbaticals.
- Paid parental leave, family support, retirement matching, and employee equity.
- Learning and development programs, wellness and home office stipends, and access to AI tools.
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