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Executive Insurance Data Analytics Jobs in Kansas

The ability to translate business needs into practical data solutions If you've been looking for a role that combines insurance expertise, analytics, and process improvement, additional details are ...

The ability to translate business needs into practical data solutions If you've been looking for a role that combines insurance expertise, analytics, and process improvement, additional details are ...

The ability to translate business needs into practical data solutions If you've been looking for a role that combines insurance expertise, analytics, and process improvement, additional details are ...

Build trusted relationships with department heads, regional leaders, and senior executives * Translate business questions into analytical briefs and data requirements for the technical team

... and executive-ready narratives for what changed, why it changed, and what to do next * Analyze ... Design and validate analytics tracking for new features, live events, player offers, and ...

Data Engineer

Overland Park, KS ยท On-site

$111K - $133K/yr

The insurance industry has not evolved with innovation like other major industries. We're here to ... Collaborate with developers, data scientists, analysts, and others to support data-related ...

Data Engineer

Overland Park, KS ยท On-site

$111K - $133K/yr

The insurance industry has not evolved with innovation like other major industries. We're here to ... Collaborate with developers, data scientists, analysts, and others to support data-related ...

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Executive Insurance Data Analytics information

What is an executive insurance data analytics?

An Executive Insurance Data Analytics professional is a senior leader who oversees the collection, analysis, and interpretation of data to guide decision-making within insurance organizations. They leverage advanced analytics, data science, and business intelligence to identify trends, assess risks, and optimize business strategies. Their role often involves setting data strategy, ensuring data quality, and communicating insights to stakeholders to improve profitability and efficiency. They typically collaborate with IT, actuarial, underwriting, and claims teams to drive data-driven transformation across the company.

How does an executive insurance data analytics typically collaborate with other departments to drive business decisions?

In the Executive Insurance Data Analytics role, collaboration with departments such as underwriting, claims, and product development is essential. You will regularly work with cross-functional teams to interpret complex data, identify trends, and provide actionable insights that support strategic business decisions. Clear communication and the ability to translate analytics into business terms are key, as you will often present findings to both technical and non-technical stakeholders. This collaborative approach not only helps improve operational efficiency but also ensures data-driven decision-making across the organization.

What are the key skills and qualifications needed to thrive as an executive insurance data analytics, and why are they important?

To excel as an Executive in Insurance Data Analytics, you need expertise in statistical analysis, data modeling, insurance industry knowledge, and often an advanced degree in data science or actuarial science. Familiarity with analytics platforms like SAS, SQL, Python, and business intelligence tools, as well as certifications such as CPCU or data analytics credentials, are typically required. Strategic thinking, leadership, and strong communication skills help drive insights and influence organizational decision-making. These skills are crucial for transforming complex data into actionable strategies that enhance profitability and manage risk in the insurance sector.

What is the difference between Executive Insurance Data Analytics vs Insurance Data Analyst?

AspectExecutive Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's or higher in Data Science, Statistics, or related field; experience in insurance analyticsBachelor's in Data Science, Statistics, or related field; entry to mid-level experience
Work EnvironmentStrategic, leadership-focused, often in management teamsOperational, data-focused, often in analytics teams
Employer & Industry UsageInsurance companies, consulting firms, risk management firmsInsurance companies, brokers, third-party analytics providers

Executive Insurance Data Analytics roles focus on strategic decision-making and leadership in insurance data projects, while Insurance Data Analysts handle data collection, analysis, and reporting at operational levels. Both roles require similar educational backgrounds but differ in scope and responsibility.

What are the most commonly searched types of Insurance Data Analytics jobs in Kansas?

The most popular types of Insurance Data Analytics jobs in Kansas are:

What cities in Kansas are hiring for Executive Insurance Data Analytics jobs?

Cities in Kansas with the most Executive Insurance Data Analytics job openings:

Senior Director, Data & Analytics Engineering

Quality Technology Services, LLC

Overland Park, KS โ€ข On-site

Full-time

Posted 25 days ago


Job description

As the Senior Director of Data & Analytics Engineering, you will serve as a senior technology leader responsible for defining and executing the enterprise vision, strategy, and operating model for data and analytics engineering across QTS. You will provide strategic leadership for the architecture, governance, scalability, and modernization of the enterprise data ecosystem, ensuring data becomes a foundational asset that accelerates business growth, operational excellence, and AI-driven innovation.

This role leads multiple teams and technical leaders responsible for building and operating modern, AI-enabled data platforms that power enterprise analytics, business operations, executive decision-making, and future digital capabilities. You will shape long-term data and AI investments, influence enterprise technology strategy, and partner closely with executive leaders across Product, Technology, Finance, Operations, and Business Functions to transform how data is sourced, governed, activated, and consumed across the organization.

As a key leader within the Enterprise Data & Analytics organization, you will establish strategic priorities, develop organizational capability, and champion modern engineering practices that position QTS to scale effectively while maximizing the value of data, analytics, and artificial intelligence.


What You Will Do: (Job Responsibilities)

  • Define and drive the long-term enterprise vision and strategy for data and analytics engineering, ensuring alignment with corporate growth objectives, digital transformation initiatives, and business strategy.
  • Serve as a trusted advisor to executive leadership, influencing enterprise decisions related to data, analytics, AI, governance, and technology investments.
  • Establish organizational priorities, operating models, and investment strategies that optimize platform scalability, business value delivery, and technology modernization.
  • Lead and develop a multi-layered organization of engineering managers, architects, and technical leaders, building leadership bench strength and succession plans for critical roles.
  • Design and evolve the organizational structure, talent strategy, and operating model required to support rapid business growth and emerging technology needs.
  • Manage departmental budgets, vendor relationships, and strategic technology investments to ensure effective allocation of resources and achieve business outcomes.
  • Drive enterprise-wide adoption of data products, governance standards, AI capabilities, and self-service analytics through partnership with senior business and technology leaders.
  • Establish and champion enterprise standards, architectural principles, and data governance frameworks that enable consistency, compliance, and scalability across business functions.
  • Represent the Data & Analytics function in executive forums, strategic planning sessions, and enterprise transformation initiatives.
  • Other duties as assigned.
  • Min. 11 years of experience in data engineering, analytics engineering, or data platform leadership, including 5+ years leading managers or senior technical teams.
  • 15+ years of progressive experience in data engineering, analytics engineering, data platforms, or enterprise technology leadership, including 8+ years leading managers, senior leaders, and large-scale engineering organizations.
  • Demonstrated success defining and executing enterprise-wide data, analytics, or digital transformation strategies across complex, rapidly scaling organizations.
  • Experience leading through multiple layers of leadership, including managers, senior managers, architects, and technical leads.
  • Proven ability to influence executive stakeholders and drive alignment across business, product, operations, and technology organizations.
  • Experience managing significant budgets, technology investments, vendor relationships, and strategic sourcing decisions.
  • Track record of building and scaling high-performing organizations while driving organizational change, capability development, and succession planning.
  • Experience presenting technology strategies, business cases, investment recommendations, and transformation roadmaps to executive leadership teams and Board-level audiences.
  • Deep expertise in architecting, scaling, and governing modern cloud-based data platforms, including data warehousing, ingestion, transformation, semantic modeling, and data product frameworks, with extensive experience leveraging technologies such as Snowflake, Fivetran, dbt, and contemporary ELT ecosystems.
  • Demonstrated expertise in modern streaming and near-real-time data architectures, including Kafka, CDC, and dynamic data processing patterns, with the ability to evaluate, prioritize, and implement solutions that enable business agility and data-driven decision-making.
  • Extensive experience with software engineering best practices and agile delivery (sprint planning, code review, testing, CI/CD, on-call, postmortems).
  • Strong understanding of enterprise analytics and data consumption strategies, including BI and visualization platforms such as Tableau, Looker, or similar tools, with the ability to influence stakeholders and align analytical capabilities to business objectives.

We conform to all the laws, statutes, and regulations concerning equal employment opportunities and affirmative action. We strongly encourage women, minorities, individuals with disabilities and veterans to apply to all of our job openings. We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, or national origin, age, disability status, Genetic Information & Testing, Family & Medical Leave, protected veteran status, or any other characteristic protected by law. We prohibit retaliation against individuals who bring forth any complaint, orally or in writing, to the employer or the government, or against any individuals who assist or participate in the investigation of any complaint or discrimination claim.

The "Know Your Rights" Poster is included here:

Know Your Rights (English)

Know Your Rights (Spanish)

The pay transparency policy is available here:

Pay Transparency Nondiscrimination Poster-Formatted

QTS is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to talentacquisition@qtsdatacenters.com and let us know the nature of your request and your contact information.