Senior Analytics Engineer

Simon & Schuster; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Simon & Schuster is seeking a Senior Analytics Engineer to turn commitments into trusted, reusable data products across publishing, sales, marketing, finance, and operations. This role blends analytics engineering, business partnership, and responsible AI to deliver governed models, consistent metrics, and scalable self-service analytics.

You will build data products, define critical measures, and apply automated testing and data-quality controls to ensure reliable outputs while partnering with

Qualifications

• 5+ years in analytics engineering, data engineering, BI engineering, or related data role.

Responsibilities

• Build trusted data products and scalable transformation pipelines, dimensional models, curated data marts, and reusable datasets for reporting, forecasting, experimentation, and AI-enabled use cases.
• Create consistent metrics by partnering with business leaders to define measures and encode business logic for shared definitions across dashboards and analyses.
• Engineer for trust with automated testing, documentation, lineage, monitoring, code review, and data-quality controls.
• Enable responsible AI by using approved AI tools to prepare governed data for AI applications and validate outputs for accuracy and business fit.
• Automate manual processes by replacing repetitive data-intensive workflows with reliable, monitored automation that improves speed and control.
• Modernize analytics by transitioning legacy reporting into governed data products and self-service experiences while controlling platform cost.
• Lead through influence, translate ambiguous questions into practical solutions, and mentor colleagues to raise engineering standards.
• Partner across the enterprise with stakeholders in publishing, sales, marketing, finance, operations, supply chain, and technology.
• Drive adoption by documenting solutions and coaching users to interpret and apply data in business terms.

Skills

Advanced SQL

Dimensional modeling

Snowflake

dbt

Python

Git

CI/CD

Power BI

Tableau

Looker

Education

Bachelor’s degree in a quantitative or technical field

Tools

Snowflake

dbt

Git

Python

Power BI

Tableau

Looker

CI/CD tooling

Job description

We are seeking a Senior Analytics Engineer to help turn that commitment into trusted, reusable data products across publishing, sales, marketing, finance, and operations. This senior hands-on role combines analytics engineering, business partnership, and responsible use of AI to deliver governed data models, consistent metrics, and scalable self-service analytics.

Responsibilities:

• Build trusted data products. Develop scalable transformation pipelines, dimensional models, curated data marts, and reusable datasets for reporting, forecasting, experimentation, and AI-enabled use cases.
• Create consistent metrics. Partner with business leaders to define critical measures and encode consistent business logic so teams work from shared definitions across dashboards, analyses, applications, and AI experiences.
• Engineer for trust. Apply automated testing, documentation, lineage, monitoring, code review, and data-quality controls; resolve issues at their root cause.
• Enable responsible AI. Use approved AI tools to accelerate delivery, prepare governed data for AI applications, and validate generated outputs for accuracy, explainability, and business fit.
• Automate manual processes. Partner with business and operations teams to replace repetitive, data-intensive workflows with reliable, monitored automation that improves speed, accuracy, control, and employee capacity.
• Modernize analytics. Transition fragmented or legacy reporting into governed data products and self-service experiences while maintaining business continuity and controlling platform cost.
• Lead through influence. Translate ambiguous questions into practical solutions, communicate recommendations clearly, mentor colleagues, and raise team engineering standards.
• Partner across the enterprise. Work with stakeholders in publishing, sales, marketing, finance, operations, supply chain, and technology, including globally distributed colleagues.
• Drive adoption. Document solutions, explain data products in business language, and coach users to confidently interpret and apply data

Requirements:

• 5+ years in analytics engineering, data engineering, BI engineering, or a related data role.
• Advanced SQL, dimensional modeling, and experience with structured and semi-structured data.
• Hands-on experience with a modern cloud data platform and transformation framework, such as Snowflake and dbt or comparable technologies.
• Practical Python skills and experience with Git, modular design, testing, code review, CI/CD, and production support.
• Experience defining governed business metrics and delivering analytics through Power BI, Tableau, Looker, or a comparable platform.
• Strong business partnership, communication, and problem-solving, with sound judgment around sensitive data and AI-assisted tools.
• Experience mentoring colleagues and improving team practices through feedback and shared standards.

Preferred:

• Experience with semantic layers, observability, metadata, lineage, or data contracts.
• Experience with commercial, supply chain, and marketing analytics
• Experience modernizing legacy reporting and enabling governed self-service analytics.
• Familiarity with generative AI, or AI-product evaluation.
• Publishing, media, retail, or consumer-products experience
• Bachelor's degree in a quantitative or technical field, or equivalent practical experience.