Lead Analytics Engineer: AI-Native Self-Service Analytics

Scribd, Inc.; Austin (CO); On-site; USD 149,000 - 250,000; Full time

Benefits offered by this job

Scribd Flex (flexible work model)

Comprehensive health, dental, vision

Generous PTO and holidays

Parental leave & family support

Retirement matching & equity

Learning & development programs

Wellness & home office stipends

AI tools access

Job summary

Scribd, Inc. is seeking a Principal/Lead Analytics Engineer to scale data foundations and governance for an AI-native environment. You will guide modeling standards, architecture, and developer experience, influencing data products across teams.

You will partner with Analytics Engineering, Data Science, and product teams to ensure trusted, scalable data assets, with a focus on reliability and measurable business impact. This role requires strategic judgment and hands-on leadership.

Qualifications

• 10+ years of experience in analytics engineering or related discipline.
• Experience building governed data models and semantic layers.
• Experience designing data quality, observability, governance, and lineage systems.
• Experience leading data initiatives from strategy to production adoption.

Responsibilities

• Shape technical foundations, modeling standards, and development practices.
• Lead cross-functional data initiatives from strategy through production adoption.
• Communicate tradeoffs to senior leaders and align investments to priorities.
• Focus on data quality, governance, accessibility, and developer experience.
• Iterate with pragmatic sequencing to move teams forward.

Skills

Analytics engineering

Data governance

SQL

Data modeling

Semantic layers

AWS

Databricks

Looker

Cross-functional leadership

Communication

Tools

AWS

Databricks

Airbyte

Fivetran

Looker

Job description

Scribd, Inc. is seeking a Principal/Lead Analytics Engineer to scale data foundations and governance for an AI-native environment. You will guide modeling standards, architecture, and developer experience, influencing data products across teams.

You will partner with Analytics Engineering, Data Science, and product teams to ensure trusted, scalable data assets, with a focus on reliability and measurable business impact. This role requires strategic judgment and hands-on leadership.