Sr. Data Analyst

Job Title

Sr. Data Analyst

Job Type

Contract

Duration

4 Months

Location

Seattle, WA 98101

Hybrid role - 4 days onsite/week

Overview

We’re committed to using data, automation, and AI to operate smarter, move faster, and better serve our customers. role supports a portfolio of enterprise programs that modernize how Finance operates by transforming insights delivery, automating manual work, and embedding AI into everyday financial processes. You will partner closely with Finance, Technology, Data & Analytics, and Business teams to deliver scalable analytics and AI solutions that improve efficiency, increase transparency, and enable better decisions across the company.

Job Description

A day in the life

• Support and deliver analytics products that advance finance automation, analytics modernization, data governance, and AI enablement across cross-functional business initiatives.
• Partner with Finance and Technology teams to design scalable analytical solutions, including semantic data models, self-service reporting, AI-assisted analysis, reconciliations, variance explanations, forecasting, and accelerated close and management reporting processes.
• Work with data engineering, analytics, and AI teams to define business requirements, design analytical datasets and semantic layers, and move solutions from concept to production, ensuring they are secure, explainable, governed, and fit for enterprise use.
• Design and maintain scalable, reliable, and intuitive analytics solutions, leveraging dimensional modeling, standardized metrics, and reusable data assets to improve adoption, efficiency, and visibility into financial performance.
• Partner with Finance, Data & Analytics, and business stakeholders to reduce manual effort, streamline finance workflows, standardize business definitions, and identify opportunities where automation and AI can unlock capacity and improve decision-making.
• Manage multiple stakeholder groups and project workstreams by aligning requirements, prioritizing work, identifying risks and dependencies, driving decisions, and communicating progress, tradeoffs, and outcomes clearly to leadership and partners.

Skills

You own this if you have

• Bachelor's degree in a quantitative field (e.g., Analytics, Statistics, Computer Science, Economics, Engineering) and 5 years of experience delivering analytics solutions, data products, and business insights in complex, cross-functional environments.
• Hands-on experience designing and implementing analytical data models in a modern data warehouse (e.g., BigQuery, Snowflake, Redshift, Synapse, or equivalent), including dimensional modeling, fact and dimension tables, business-friendly data marts, semantic layers (e.g., LookML), and governed metric definitions.
• Deep hands-on fluency with SQL and BI/visualization platforms (e.g., Looker, Tableau, Oracle Analytics, Power BI, or equivalent), including translating business requirements into scalable reporting models, reusable metrics, dashboards, and self-service analytics experiences; Python or R experience is a plus.
• Experience designing and using AI-enabled workflows (e.g., LLM-assisted analysis, prompt-driven reporting, conversational analytics, or agentic automation) to accelerate analytics delivery, with sound judgment on validating AI outputs for accuracy, explainability, and governance.
• Experience partnering with data engineering and platform teams to develop and operationalize analytical datasets, data pipelines, data quality controls, metadata, governance practices, and scalable reporting architectures.
• Strong analytical storytelling and communication skills, with the ability to translate complex data into actionable insights for technical and non-technical audiences and influence decisions across business, finance, and technology stakeholders.
• Experience building automated analytics, monitoring, alerting, or insight-generation solutions, and applying analytics to finance, accounting, or retail business processes; experience supporting financial reporting, forecasting, variance analysis, or close processes is preferred.