The Senior Data Analyst turns complex data into clear, actionable insights that drive financial and operational outcomes. In this role, you will develop scalable analytics assets for finance and revenue cycle management, connect operational activity to financial performance, and partner independently with executive stakeholders on high-impact data problems. You will build reliable data products, conduct exploratory analysis, and translate findings into recommendations that create measurable business value.
Do you enjoy building systems you can take pride in, discovering insights that create measurable value, and working in a role that is both business-facing and technical? If you want to grow your data career with mentorship, resources, and meaningful ownership, this could be a great role for you.
The primary tools used in this role are Databricks, SQL, R, Power BI, and related Microsoft Fabric capabilities.
Remote hires will be required to travel to our headquarters in Ankeny, IA (company paid) their first few days for new hire orientation, training, and onboarding.
At this time, we are NOT considering applicants that require immigration sponsorship (additional work authorization or permanent work authorization) now or in the future to work in the United States. This includes, but IS NOT LIMITED TO: F1-OPT, F1-CPT, H-1B, TN, L-1, J-1, etc.
Salary range: $101,700-113,000 plus 10% bonus
Benefits
Our employees enjoy a generous package of benefits that we are thrilled to provide, and feel is part of what makes us different as an employer. We value our team members, and this is one way we can show it.
Benefits include:
-PTO, holiday pay and holiday of choice
-401(k) match
-Life insurance
-Short-term disability
-Health, dental and vision insurance
-Maternity/paternity leave
-Health savings account (HSA)
-Flex spending accounts (FSA) – health and dependent
Position Responsibilities may include, but not limited to
- Support high-impact analytics initiatives from problem framing through delivery; quantify value, design robust analyses, and communicate recommendations to business partners and executives
- Partner with finance and revenue cycle management stakeholders to develop new self-service reporting tools and capacities
- Develop core organizational KPIs and directly present on the success and health of our business to senior stakeholders
- Develop analytics products and solutions using Databricks, dbt, custom scripting, and BI tools
- Implement advanced analytics where applicable, using scalable scripts and Databricks workflows to support modeling, automation, and repeatable analysis
- Build performant Databricks workflows (notebooks, jobs, SQL Warehouses) to wrangle large datasets, engineer features, and automate recurring analyses
- Partner with Data Engineering to design scalable data solutions, clarify upstream data requirements, and ensure analytics assets are built on reliable data foundations
- Own analysis quality through data validation, experiment and study design, sensitivity checks, reproducibility, versioning, and documentation
- Define and monitor KPIs tying operational reporting directly to business objectives
- Adopt and champion BI development standards across the organization, including naming conventions, documentation expectations, quality checks, and release practices
- Stay current with emerging analytics methodologies, technologies, and capabilities
Required Skills and Experience
- 4-8 years in analytics roles, including 2+ years leading projects with cross-functional business stakeholders
- 2+ years writing data directly to a data warehouse
- 2+ years partnering directly with finance, strategy and ops, FP&A, or revenue cycle management leaders
- Proven impact delivering analytics in complex environments (messy data, ambiguous scope) with measurable business outcomes
- Statistical and financial analytics expertise, including analysis design, interpretation of results, and business case development
- Expert proficiency in writing production-level SQL with query optimization over large, partitioned tables
- Knowledge of AI-assisted analytics development, and AI-assisted analytics tools
- Versioning and Reproducibility: Git‑based workflows; disciplined documentation, and peer review
- Comfort in at least one BI platform like Power BI, Hex, Tableau, etc.
- Proficiency in R to create reproducible workflows, conduct statistical testing, and develop basic models
- Executive storytelling: translate complex analyses into clear narratives, recommended actions, and solutions that support decision-making
- Stakeholder partnership: influence cross-functional partners, set expectations, drive alignment, and maintain trust through clear communication
- Product mindset: understand and define problem statements, success metrics, and iterate with feedback – drives adoption of analytics products and solutions
Preferred Skills and Experience
- Certifications in Databricks, dbt, Power BI, or cloud platforms (Azure preferred)
- Familiarity with data governance tools and compliance standards
- Product management training or analytics product delivery experience
Physical Requirements
- Repetitive motions that include the wrists, hands and/or fingers
- Sedentary work that primarily involves sitting, remaining in a stationary position for prolonged periods
- Visual perception to perform job including peripheral vision, depth perception, and the ability to adjust focus
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
