Lead Analytics Engineer — Payments, Identity & Trust and Safety

Scribd, Inc.•Vancouver, BC

1d•$149,000 - $253,500

About The Position

Scribd, Inc.’s Data & Analytics organization combines Analytics Engineering, Data Science, and Data Analytics to create trusted, production-quality data foundations and AI-enabled decision tools. This is the senior-most analytics engineering role supporting payments, identity, security, and Trust & Safety. It is a technical leadership position with no direct reports, reporting to the Director, Analytics Engineering, and working closely with Product Analytics, Data Science, Product, and Engineering. The role establishes authoritative definitions for core business concepts and ensures metrics remain reliable through processor migrations, schema changes, and market launches. For Trust & Safety, it develops consistent measurements of violating content and user exposure as moderation models, policies, and review processes evolve. Metric definitions are treated as engineering artifacts, with emphasis on lineage, observability, and data quality. The Lead Analytics Engineer owns canonical data models for payments, billing, and subscriptions across Scribd, Everand, and Fable; the KPI and semantic layer for payments and identity; and Trust & Safety models and metrics for prevalence and exposure, including evaluation of AI-generated moderation labels. The role also builds AI tools grounded in certified data and metrics, establishes modeling and metric conventions, influences source-system changes, and mentors analysts and analytics engineers. Compensation includes a competitive equity ownership opportunity and a comprehensive benefits package.

Requirements

At least 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 providers.
Practical experience with identity and authentication data.
Depth in governed, canonical data models and semantic layers, with a track record of defining metrics, defending them under scrutiny, and versioning them when their inputs change.
Advanced SQL skills 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.

Nice To Haves

Advanced Python and experience building AI agents or LLM-based pipelines.
Experience with Trust & Safety or integrity measurement.
Experience with local payment methods across LATAM, APAC, or EU markets, and with stored-credential and network compliance frameworks.
Experience with on-call rotations and incident response for production data systems.

Responsibilities

Own canonical Databricks data models for payments, billing, and subscriptions across Scribd, Everand, and Fable, designed to accommodate new markets and payment methods without rewrites.
Own the KPI and semantic layer for payments and identity, exposed through self-serve dashboards and AI tools.
Own Trust & Safety models and metrics for content prevalence and exposure, including evaluation of AI-generated moderation labels.
Drive data quality, observability, and lineage; detect changes such as login challenge rate or processor routing changes promptly and investigate discontinuities to distinguish real behavior from migration artifacts and data quality issues.
Build AI tools on trusted foundations, grounded in certified metrics and tables, synchronized with definition changes, and validated with evaluation sets.
Set modeling and metric conventions, raise the technical bar, and influence source-system changes before they land.
Mentor analysts and analytics engineers in the supported domains.
Communicate methodology and document models and metrics.
Translate complex payment economics into clear business trade-offs for senior product and engineering leaders.

Benefits

Scribd Flex flexible work model.
Comprehensive health, dental, and vision coverage.
Mental health support and disability coverage.
Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals.
Paid parental leave and family support benefits.
Retirement matching and employee equity.
Learning and development programs and professional growth opportunities.
Wellness and home office stipends.
Complimentary access to the Scribd, Inc. suite of products.
Enterprise access to leading AI tools.
Competitive equity ownership opportunity.