Senior Analytics Engineer

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.

Skills

Analytics, BI, Business Intelligence, Report, Reports, SQL, Snowflake, dbt