Senior Analytics Engineer, AI-Native Self-Serve Analytics

Scribd, Inc.; Boston (MA); Sur place; USD 149 000 - 250 000; Plein temps

Avantages offerts par ce poste

Scribd Flex (flexible work model)

Comprehensive health, dental, and vis

Paid time off including holidays

Résumé du poste

Scribd, Inc. is seeking a Principal & Lead Analytics Engineer to scale data for an AI-native platform. You will shape the technical foundations, modeling standards, and development practices that enable faster, more confident progress across teams.

Your role combines strategic judgment with hands-on execution, guiding data architecture, governance, and quality while delivering reliable analytics for product and business decisions.

Qualifications

• 10+ years of experience in analytics engineering or related field.
• Governed data models and semantic layers with authoritative definitions.
• Design data quality, observability, governance, and lineage systems.
• Lead cross-functional data initiatives from strategy to production.
• Advanced SQL and experience with modern data stack (AWS/Databricks/Looker).
• Strong judgment balancing immediate needs with reusable data products.

Responsabilités

• Lead analytics engineering initiatives and define standards.
• Shape technical foundations, modeling, and development practices.
• Guide decisions on data architecture, governance, and quality.
• Collaborate with product, tech, and business teams to enable analytics.
• Drive measurable business impact through scalable data products.

Connaissances

Analytics engineering

Data modeling

SQL proficiency

Data governance

Cross-functional leadership

AWS/Databricks

Looker

Outils

AWS

Databricks

Looker

Fivetran

Airbyte

Description du poste

Scribd, Inc. is seeking a Principal & Lead Analytics Engineer to scale data for an AI-native platform. You will shape the technical foundations, modeling standards, and development practices that enable faster, more confident progress across teams.

Your role combines strategic judgment with hands-on execution, guiding data architecture, governance, and quality while delivering reliable analytics for product and business decisions.