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Salary: USD 149,000 - 253,500 / annual
Scribd, Inc. is seeking a senior analytics engineer to own the data foundations for payments, identity, security, and trust & safety systems. This is a purely technical leadership role with no direct reports, reporting to the Director of Analytics Engineering.
You will work embedded with Product Analytics, Data Science, Product, and Engineering teams to establish authoritative definitions for core business concepts and ensure data reliability across migrations, schema changes, and market launches. For Trust & Safety, you'll develop metrics to measure violating content prevalence and user exposure with consistency across changing moderation models and policies.
Key responsibilities include:
- Owning canonical data models for payments, billing, and subscriptions in Databricks, modeled once across Scribd, Everand, and Fable to support new markets and payment methods without rewrites
- Owning KPI and semantic layers for payments and identity exposed through self-serve dashboarding and AI tools
- Extending data discipline to Trust & Safety, owning models and metrics for prevalence and exposure, including evaluation of AI-generated moderation labels
- Driving quality, observability, and lineage to catch regional or processor changes within days, not quarters
- Building AI tools on trusted foundations grounded in certified metrics and validated evaluation sets
- Raising technical standards, setting modeling conventions, influencing source-system changes, and mentoring analysts and engineers
The role emphasizes that metric definitions are engineering artifacts requiring attention to lineage, observability, and data quality. You will be skeptical by default, pragmatic in approach, and focused on preventing silent data breaks upstream.
Requirements:
- 8+ years of experience in analytics engineering, data engineering, business intelligence engineering, or related discipline
- Deep, hands-on payments expertise with direct experience from Stripe, Adyen, Braintree, PayPal, or similar processors
- Practical experience with identity and authentication data
- Depth in governed, canonical data models and semantic layers; proven track record of defining metrics, defending them under scrutiny, and versioning when 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
Nice to have:
- Advanced Python and experience building AI agents or LLM-based pipelines
- Experience with trust and 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
