Analytics Engineering Lead — Payments & Trust AI

Scribd, Inc.; Boston (MA); Hybrid; USD 149,000 - 241,000; Full time

Benefits offered by this job

Scribd Flex

Health, dental, and vision coverage

Generous paid time off

Equity

Learning and development

Wellness stipend

Job summary

Scribd, Inc. in Boston, MA is seeking a Senior Analytics Engineer to own canonical data models for payments, billing, and subscriptions, and to lead KPI and semantic layers across teams.

You will work in the Data & Analytics group embedded with Product Analytics, Data Science, Product, and Engineering; this role emphasizes data quality, observability, and governance to enable reliable AI-powered insights and decision making.

Qualifications

• 8+ years of experience in analytics engineering, data engineering, BI engineering, or related discipline.
• Deep payments expertise with processor data from Stripe/Adyen/Braintree/PayPal or similar.
• Experience with identity and authentication data.
• Proven ability to define, defend, and version a metric.

Responsibilities

• Own canonical data models for payments, billing, and subscriptions across Scribd, Everand, and Fable.
• Own KPI and semantic layer for payments and identity via self-serve dashboards/AI tools.
• Extend discipline to Trust & Safety, owning models and metrics for prevalence and exposure.
• Drive quality, observability, and data lineage to catch issues early.
• Build AI tools on trusted foundations with validated evaluation sets.
• Mentor analysts and analytics engineers in modeling conventions and definitions.

Skills

Analytics engineering

Data engineering

SQL

Databricks

AWS

Looker

Data modeling

Tools

Databricks

AWS

Looker

Airbyte

Fivetran

Job description

Scribd, Inc. in Boston, MA is seeking a Senior Analytics Engineer to own canonical data models for payments, billing, and subscriptions, and to lead KPI and semantic layers across teams.

You will work in the Data & Analytics group embedded with Product Analytics, Data Science, Product, and Engineering; this role emphasizes data quality, observability, and governance to enable reliable AI-powered insights and decision making.