Principal Data Analysis

This is a full-time onsite role based in the location(s) posted and is performed from the designated work location five days per week. No relocation is offered.

The Principal Data Analyst leads the design and execution of complex analytics initiatives that transform enterprise data into strategic business insights and measurable outcomes. This role provides technical and thought leadership across advanced analytics, business intelligence, data management, governance, and emerging AI capabilities.

As a strategic advisor and recognized subject matter expert (SME), the Principal Data Analyst contributes to enterprise data strategy, leads business-critical initiatives, mentors analytics professionals, and advises senior leaders on complex decisions. This individual applies modern technologies—including cloud data platforms, predictive analytics, machine learning, and AI-assisted solutions—to solve complex business challenges and advance the organization’s analytical capabilities. Experience with Databricks and/or Snowflake is highly desirable.

Responsibilities may include, but are not limited to:

• Enterprise Analytics Leadership: Lead complex, enterprise-wide analytical initiatives that translate data into actionable strategies, measurable outcomes, and business value.
• Data Analysis and Interpretation: Apply advanced statistical and analytical methods to identify trends, relationships, risks, and opportunities. Translate findings into clear recommendations for senior leaders and other stakeholders.
• Data Strategy and Roadmaps: Partner with business and technology leaders to define data strategies, analytical roadmaps, key performance indicator frameworks, and measurement plans.
• Advanced Analytics and AI: Develop or guide the implementation of predictive models, forecasting solutions, machine-learning applications, and AI-assisted insights that improve decision-making and operational performance.
• Business Intelligence and Visualization: Design and oversee executive dashboards, reporting solutions, and visualizations that communicate complex information clearly, accurately, and persuasively.
• Data Integration and Architecture: Provide technical direction for large-scale data integration, data modeling, ETL/ELT pipelines, data warehouses, and lakehouse architectures.
• Data Quality and Governance: Establish and promote practices for data quality, governance, metadata management, lineage, auditing, and discrepancy resolution across platforms and data domains.
• Technology Evaluation and Modernization: Evaluate emerging technologies and architectural approaches, including generative AI, machine learning, cloud data platforms, and advanced analytics tools. Recommend solutions aligned with business objectives and technical standards.
• Stakeholder Partnership: Collaborate with business, technology, architecture, governance, and data teams to define requirements, resolve complex challenges, and deliver scalable analytical solutions.
• Technical Leadership and Mentoring: Establish analytical best practices, provide guidance on challenging technical issues, conduct solution reviews, and mentor analytics professionals.
• Executive Communication: Present findings, recommendations, risks, and strategic options to senior leaders in a concise and business-focused manner.

A recognized expert who applies extensive technical expertise, broad business knowledge, and strategic insight to address highly complex challenges and deliver organizational results. Leads critical, high-impact initiatives and develops innovative analytical strategies and solutions.

Works with minimal oversight, regularly advises senior leaders, and influences significant technical and business…