Sr. Data Analyst

Spectraforce

Seattle, WA, United States

1 day ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

leoforce.us

Tech stack

Artificial Intelligence Data Analysis BigQuery Information Engineering Python (Programming Language) Oracle (Applications) SQL Databases Tableau (Software) Large Language Models Information Technology Data Analytics Looker Analytics

+1 more

Data Pipelines

Job description

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.
Support the analytical needs of cross-functional programs focused on finance automation, analytics modernization, and AI enablement.
Partner with Finance and Technology teams to deliver process automation, self-service reporting, AI-assisted analysis, reconciliations, variance explanations, forecasting, and faster close and management reporting cycles.
Work with data engineering, analytics, and AI teams to move solutions from concept to production, ensuring they are secure, explainable, and fit for enterprise use.
Design solutions for scale, reliability, and ease of use, with adoption and efficiency gains as core success measures and improved visibility into financial performance as the outcome.
Work with cross functional partners to reduce manual effort, streamline finance workflows, and standardize processes, serving as a trusted thought partner on how technology and AI can unlock capacity.
Support multiple stakeholder groups and project workstreams: track priorities, flag risks and issues that need decisions, and communicate progress clearly to the team and leadership.

Requirements

5+ years of experience delivering analytics, data products, and business insights in complex, cross-functional environments.
Hands-on data modeling experience in an analytics data warehouse (e.g., BigQuery or equivalent), including building semantic layers (e.g., LookML).
Deep hands-on fluency with SQL and BI/visualization tooling (e.g., Looker, Oracle, Tableau, or equivalent); comfort with Python or R is a plus.
Experience designing and using AI-enabled workflows (e.g., LLM-assisted analysis, prompt-driven reporting, or agentic automation) to accelerate analytics delivery, with sound judgment on validating AI outputs for accuracy and governance.
Experience partnering with data engineering/platform teams on data pipelines, quality, and governance.
Strong analytical storytelling and communication skills, with the ability to translate data into clear insights for both technical and non-technical stakeholders and to build effective working relationships across teams.
Experience with automated analytics, monitoring, or alerting solutions, and exposure to AI-assisted or conversational analytics; finance or accounting experience is a plus.
A bachelor’s degree in a quantitative field (e.g., Analytics, Statistics, Computer Science, Economics, Engineering)

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