Executive Insurance Data Analytics Jobs in Arizona

Come for the Challenge. Stay for the Experience.

At HCVT, we believe every challenge presents an opportunity to positively impact our clients and people. Talented and ambitious individuals who seek limitless professional opportunities thrive at HCVT. Our team is known for its technical skill and ability to help clients address complex business issues all while investing in and supporting our people to provide a rewarding employee experience.

What We Do and Who We Serve

We offer Tax, Audit, Advisory, and Business Management services to our clients, which include private and public companies, high-net-worth individuals, and family offices. We also specialize in serving clients across the following industries: Private Equity, Real Estate & Hospitality, Media & Entertainment, High-Net-Worth Individuals, Manufacturing & Distribution, Professional Services Firms, Technology, Healthcare, Nonprofit Organizations, and Affordable Housing.

We Live Our Core Values

Our values guide us in our day-to-day interactions with our clients and each other—Integrity at our Core; Building Success Together; Passion for Excellence; and Diversity, Equity, & Inclusion. We are focused and committed to the needs of our clients and our team.

Discover How Far You Can Go.

Opportunities abound at HCVT. Our firm has experienced steady growth since its founding in 1991 and continues to expand its client service offerings, creating new opportunities for professionals to grow their careers. We make significant investments in training and provide interesting, diverse, and intellectually stimulating work for our teams—the kind of work that helps you develop and refine your skills to advance in the profession.

Hybrid Work

HCVT currently offers a hybrid work model that allows eligible employees to work both remotely and in the office, based on business needs and team coordination. When working remotely, employees are expected to meet the same performance standards, adhere to the same policies, and maintain the same level of communication, collaboration, and responsiveness as working in the office. Please note that this arrangement is not guaranteed and subject to change at any time. We will strive to provide reasonable notice of any changes to your work location or schedule whenever possible.

The Senior Data & Analytics Specialist is responsible for designing, building, and advancing the firm’s enterprise data and analytics capabilities. This role combines expertise in data engineering, business intelligence, advanced analytics, and machine learning to deliver scalable data platforms, actionable business insights, and AI-ready data assets. Working closely with business and technology leaders, the position transforms enterprise data into trusted information that improves decision‑making, operational efficiency, and client outcomes.

• Enterprise Data Platform & Engineering: Design, develop, and maintain the firm’s enterprise data platform, including data warehouses, data lakes, semantic models, and data pipelines. Build scalable ETL/ELT processes that integrate information across Finance, Tax, Audit, Advisory, Operations, and other business systems while ensuring data quality, reliability, governance, and performance. Define data models, standards, and architecture that support reporting, analytics, machine learning, and AI initiatives.
• Data Analytics & Business Intelligence: Develop modern analytics solutions that provide meaningful insights into business performance and operations. Design and deliver executive dashboards, KPIs, operational reporting, and self-service analytics using Power BI and Microsoft Fabric. Partner with business stakeholders to translate analytical requirements into scalable reporting solutions while establishing best practices for data visualization, metric definitions, and analytics governance.
• Advanced Analytics & Data Science: Apply statistical analysis, predictive modeling, forecasting, and machine learning techniques to solve complex business problems. Build analytical models that improve operational efficiency, identify trends, predict outcomes, and support strategic decision‑making. Evaluate model performance, improve accuracy, and operationalize analytical solutions for enterprise use.
• AI-Ready Data & Intelligent Solutions: Develop governed, high-quality data assets that enable AI applications, intelligent automation, and generative AI solutions. Support modern AI capabilities through semantic models, vector-ready datasets, retrieval pipelines, and data preparation processes that improve the accuracy, reliability, and scalability of AI-enabled business solutions. Partner with software engineering teams to integrate analytics and machine learning capabilities into enterprise applications and AI agents.
• Technical Leadership & Data Strategy: Provide technical leadership in enterprise data architecture, analytics technologies, and modern data engineering practices. Evaluate emerging tools and technologies, recommend improvements to the firm’s data ecosystem, and contribute to the long-term analytics and AI strategy. Promote engineering best practices, data governance standards, automation, and continuous improvement across the analytics platform.

• 5+ years of progressive experience in data engineering, data analytics, data science, business intelligence, or related technical disciplines.
• Degree in Computer Science, Data Science, Analytics, Engineering, or a related technical discipline.
• Strong experience designing relational databases, dimensional models, data warehouses, and scalable data pipelines.
• Advanced proficiency with SQL and Python, including data transformation, automation, and analytical development.
• Experience designing and implementing ETL/ELT processes, data integration solutions, and enterprise data models.
• Working knowledge of statistical analysis, predictive modeling, and model evaluation techniques.
• Knowledge of DevOps, CI/CD, Git, and Infrastructure-as-Code practices for analytics platforms.
• Experience with data governance, data quality, metadata management, and enterprise analytics best practices.
• Strong analytical thinking, technical problem‑solving, and the ability to translate business requirements into scalable data solutions.
• Excellent communication skills with the ability to explain complex technical concepts to business stakeholders.

• Experience within professional services, consulting, financial services, or public accounting.
• Hands‑on expertise with Microsoft Fabric, Azure Data Platform, Power BI, or comparable cloud‑based analytics platforms.
• Experience with AI‑enabled data architectures, RAG pipelines, semantic search, vector databases, or LLM‑powered applications.
• Experience building production machine learning or advanced analytics solutions.
• Master’s Degree in Computer Science, Data Science, Analytics, Engineering, or a related technical discipline.

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