Senior Analytics Engineer — Payments & Trust Data

Scribd, Inc.; Los Angeles (CA); Hybrid; USD 179,000 - 254,000; Full time

Benefits offered by this job

Scribd Flex

Health coverage

Paid time off

Parental leave

Equity

Learning & development

Wellness stipend

AI tools access

Job summary

Scribd, Inc. is seeking an analytics engineering leader to own canonical data models for payments, billing, and subscriptions across multiple Scribd brands. You will drive KPI and semantic layers, ensure data quality, and extend capabilities to Trust & Safety with AI-focused metrics and tools.

You will build trusted data foundations, mentor teams, and influence senior leadership on data strategy, with a strong focus on observability and lineage to prevent upstream issues.

Qualifications

• 8+ years of experience in analytics engineering, data engineering, business intelligence engineering or a related discipline.
• Deep, hands-on payments expertise: including direct experience with processor data from Stripe, Adyen, Braintree, PayPal, or similar.
• Practical experience with identity and authentication data
• Depth in governed, canonical data models and semantic layers, and a track record of defining a metric, defending it under scrutiny, and versioning it when its inputs changed.
• Advanced SQL and production experience with Databricks, AWS, Looker, Airbyte, Fivetran, or comparable platforms, including orchestration, transformation frameworks, and automated testing.
• Experience making data reliable for AI consumption
• Proven ability to influence senior product and engineering leaders and translate complex payment economics into clear business trade-offs.

Responsibilities

• Own the canonical data models for payments, billing, and subscriptions in Databricks modeled once across Scribd, Everand, and Fable.
• Own the KPI and semantic layer for payments and identity exposed through self-serve dashboaring/AI tools.
• Extend the same discipline to Trust & Safety, owning the models and metrics behind prevalence and exposure.
• Drive quality, observability, and lineage to catch changes in days, not quarters.
• Build AI tools on trusted foundations, keeping definitions in sync as they change.
• Raise the technical bar, set conventions, and mentor analysts and analytics engineers.

Skills

Analytics engineering

Data engineering

Business intelligence

Payments data

Identity data

Databricks

SQL

Python

AI pipelines

Tools

Looker

Airbyte

Fivetran

AWS

Databricks

Job description

Scribd, Inc. is seeking an analytics engineering leader to own canonical data models for payments, billing, and subscriptions across multiple Scribd brands. You will drive KPI and semantic layers, ensure data quality, and extend capabilities to Trust & Safety with AI-focused metrics and tools.

You will build trusted data foundations, mentor teams, and influence senior leadership on data strategy, with a strong focus on observability and lineage to prevent upstream issues.