Director of Analytics Engineering

Scribd; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Healthcare coverage

Parental leave (12 weeks)

401k matching

Tuition reimbursement

Wellness stipend

Mental health resources

Scribd subscription

Vacation days

Job summary

Scribd is seeking a Director of Analytics Engineering to scale data foundations for an AI-native platform. You will build and lead a high-performing team, establish an operating model, and align analytics initiatives with company priorities across product, technology, content, and business.

You will drive data modeling, governance, and semantic layers, enable reliable AI and analytics tooling, and partner with senior leaders to translate strategy into scalable data products while growing talent

Qualifications

• Must lead cross-functional data initiatives from strategy through production adoption.
• Excellent written and verbal communication with executives.
• Experience designing data quality, observability, governance, and lineage.
• Proven track record of building and scaling high-performing teams.
• Strong judgment balancing immediate needs with long-term data product investments.
• Deep experience with canonical data models and semantic layers.
• Advanced SQL and modern data stack tools.
• Experience with data security, access control, and data retention.
• Experience leading on-call rotations and incident response.
• Strong partner to product and engineering leadership.

Skills

Cross-functional leadership

Excellent communication

Data quality governance

Canonical data models

Semantic layers

Advanced SQL

Python

Incident response

Team development

Strategic judgment

Education

10+ years in analytics engineering or related field

5+ years leading technical teams

Tools

Looker

Databricks

AWS

Airbyte

Fivetran

Job description

• Data & Analytics is building the DNA of an AI native Scribd, Inc. Bringing together Analytics Engineering, Data Science, and Data Analytics, D&A partners across product, technology, content, and the business to scale intelligence, advance understanding, shape strategy, and turn insight into lasting growth across our four brand portfolio
• Making this ambition real at scale starts with Analytics Engineering. The team transforms fragmented data, inconsistent definitions, and dispersed analytical knowledge into trusted, reusable, production quality data foundations and products that enable intelligence to scale across the company
• In partnership with Engineering, Analytics Engineers ensure critical data is captured, centralized, documented, secured, and governed. The team builds canonical datasets, shared metrics, and semantic layers, together with the quality, observability, lineage, and evaluation systems that make these assets trustworthy. On top of this foundation, Analytics Engineers develop AI agents and analytical tools that bring reliable intelligence directly into the decisions and workflows of teams across the company
• We’re hiring for a Director, Analytics Engineering to own scaling data for an AI native Scribd, Inc. You will build, scale, and lead a high performing Analytics Engineering team, turning strong individual contributors into a cohesive and highly effective team. This requires more than hiring and developing exceptional talent. It means establishing an operating model that creates structure without unnecessary bureaucracy, fostering culture and community that balances local priorities with the broader success of the company, and creating the technical foundations and standards of excellence that enable everyone to do their best work
• Your leadership philosophy is grounded in service. A leader’s role is to provide clarity, create context, remove obstacles, and help others succeed. You will strengthen team dynamics, ensure great work is recognized, create meaningful career pathways, and help individuals navigate obstacles and opportunities throughout their careers. Durable teams are built by distributing ownership, developing leaders, and creating an environment where people feel trusted, supported, and accountable
• Your pragmatic approach keeps the organization moving forward. Rather than waiting for an ideal end state, you will think in sequences and ask, “What is the right next version?” Communication happens early and often because transparency, thoughtful feedback, and visible decision making build trust and help teams move with confidence
• Your strong strategic judgment is paired with enough proximity to the work to guide technical decisions credibly. You will connect analytics engineering investments to company priorities, communicate tradeoffs clearly to senior leaders, and contribute thoughtfully to decisions about data modeling, architecture, governance, quality, tooling, and developer experience
• The transformation happening through AI is an opportunity to expand what talented teams can accomplish. Agentic coding, AI assisted development and analysis, and automated workflows can increase human judgment, creativity, and impact rather than replace them. You approach these technologies with curiosity and pragmatism, applying them where they create clear and measurable value
• Above all, leadership is about building people and strengthening the discipline they share. Success is reflected in a team that grows more capable, confident, connected, and effective because of your leadership

Benefits

• Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
• 12 weeks paid parental leave
• Short-term/long-term disability plans
• 401k/RSP matching
• Tuition Reimbursement
• Learning & Development programs
• Quarterly stipend for Wellness, Connectivity & Comfort
• Mental Health support & resources
• Free subscription to Scribd + gift memberships for friends & family
• Referral Bonuses
• Book Benefit
• Sabbaticals
• Company wide events
• Team engagement budgets
• Vacation & Personal Days
• Paid Holidays (+ winter break)
• Flexible Sick Time
• Volunteer Day
• Company-wide Diversity, Equity, & Inclusion programs

• 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