Senior Data Analyst

Senior Data Analyst

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Analyst based in the United States.

This is a senior individual contributor role with broad ownership over analytics for a dedicated business portfolio. You will serve as a trusted analytics partner, helping stakeholders turn complex data into clear, actionable business decisions. The role combines data governance, analytics engineering, business intelligence, and strategic insight development. You will help shape the analytics architecture using tools such as SQL, dbt, BI platforms, and AI-assisted development workflows. You will also establish reliable metrics, identify technical debt, and ensure data quality and compliance across your portfolio. Working closely with data leadership and cross-functional teams, you will influence priorities and business strategy through compelling data storytelling. This is an ideal opportunity for an experienced analyst who enjoys autonomy, meaningful ownership, and using emerging AI capabilities to work faster and smarter.

Accountabilities

• Own an analytics portfolio: Act as the primary analytics point of contact for an assigned business unit, partnering with stakeholders to understand priorities, coordinate work, and advise on data-driven decisions.
• Shape analytics strategy: Work with data leadership to identify recurring business problems, prioritize improvements, surface technical debt, and mature the analytics capabilities supporting your portfolio.
• Drive data governance: Define and maintain business metrics and KPIs, assess the impact of engineering changes on data quality, and strengthen stakeholder confidence in data through effective governance practices.
• Support compliance and data quality: Help maintain HIPAA-compliant data practices, proactively identify potential risks, and collaborate with legal, engineering, and marketing operations teams on appropriate tracking and data requirements.
• Develop analytics architecture: Design and contribute to the analytics layer using dbt and AI-assisted development tools such as Claude Code, while maintaining established data architecture and design standards.
• Translate business needs into technical solutions: Create clear technical requirements and documentation, using frameworks such as UML, and determine when existing data capabilities can be leveraged instead of building new functionality.
• Maintain analytical quality: Review code, maintain the dbt Semantic Layer as a trusted source for metric definitions, troubleshoot development issues, and create documentation that enables both stakeholders and AI tools to understand the data environment.
• Generate actionable insights: Investigate business challenges, identify meaningful patterns, develop visualizations, and present recommendations through concise, compelling data storytelling.
• Build business intelligence solutions: Create and maintain user-friendly dashboards, respond to ad hoc analytical questions, produce custom SQL reports, and support data engineering initiatives with clear requirements.
• Collaborate across functions: Build strong relationships across the organization, understand stakeholder needs, influence business strategy, and stay current with developments in AI, healthcare technology, and analytics.

Requirements

• Education: Bachelor's degree in data science, statistics, computer science, business analytics, or a related discipline, or equivalent practical experience.
• Professional experience: 7–10 years of experience in data analytics, data engineering, business intelligence, or another highly analytical function.
• Healthcare or senior analytics experience: Previous healthcare experience in BI, operations, consulting, or data science, or experience in a senior/lead analytics role focused on analytics platforms, strategy, or data governance.
• Analytical problem-solving: Demonstrated ability to solve complex, well-defined problems creatively while developing a strong understanding of business operations and proactively identifying emerging needs.
• Communication and storytelling: Strong ability to translate complex analytical findings into clear business narratives, insights, and recommendations for stakeholders.
• Technical expertise: Expert-level SQL skills and proficiency with modern business intelligence platforms such as Tableau.
• Data architecture: Familiarity with data architecture principles and technical communication frameworks such as UML, with the ability to document technical concepts clearly for non-technical audiences.
• AI fluency: Enthusiasm for learning and applying new AI tools to accelerate analysis, automate recurring workflows, and increase speed to insight.
• Additional knowledge: Familiarity with web analytics, digital marketing measurement, and HIPAA considerations related to data analytics and sharing.
• Preferred experience: Exposure to machine learning, predictive modeling, business forecasting, GitHub, dbt Cloud, Agile methodologies, Python, Jira, and Confluence.
• Working style: Strong business judgment, curiosity, autonomy, proactive stakeholder management, and the ability to anticipate needs and operate effectively in a cross-functional environment.

Benefits

• Base salary: $145,000–$180,000 annually, with final compensation determined by geographic location, skills, experience, and internal equity.
• Health coverage: Medical, dental, and vision insurance, plus long-term disability, life insurance, a Flexible Spending Account, and a 401(k).
• Paid time off: 12 company holidays, floating holidays, PTO, and a company-wide holiday shutdown between Christmas and New Year's.
• Parental support: Paid parental leave to support employees during important family milestones.
• Wellness and lifestyle: Health and wellness stipend, home office reimbursement, and commuter benefits.
• Professional development: Professional development reimbursement and license maintenance reimbursement.
• Remote flexibility: National remote work environment designed to support employees wherever they do their best work.
• Total rewards: Compensation and benefits are structured according to geographic market data and may include salary, equity, benefits, wellbeing programs, and professional growth opportunities.
• Inclusive culture: Commitment to creating an equitable and inclusive workplace where employees can contribute authentically and have equal opportunities to thrive.