Director Analytics Engineering - Life & Retirement

Title: Director Analytics Engineering - Life & Retirement Location: Remote

Horace Mann is seeking a strategic, innovative, and results-driven Director, Life & Retirement Analytical Engineering to lead the evolution of our analytical engineering capabilities and transform how data supports business decisions across our Life & Retirement organization.

In this highly influential leadership role, you'll own the strategy, delivery, and continuous improvement of analytical engineering capabilities, ensuring our business has access to trusted, scalable, and high-quality data solutions. You'll also play a key leadership role in the development of Horace Mann's enterprise data warehouse, joining this exciting initiative from the ground up and helping shape the architecture, capabilities, and foundation for future data innovation.

You'll lead and develop a team of technical professionals, establish engineering standards, and oversee a portfolio of data products that improve operational efficiency, strengthen business intelligence, and accelerate access to actionable insights.

The ideal candidate combines deep analytical engineering expertise, modern cloud-based data technologies, strong business acumen, and proven people leadership. You'll partner closely with business leaders, Analytics, Enterprise Data, Architecture, Security, and Technology teams to align technical capabilities with business priorities and drive meaningful, measurable outcomes.

Key Responsibilities

Strategic Leadership & Analytical Engineering

• Provide strategic direction and overall accountability for the Life & Retirement analytical engineering function, including people, portfolio priorities, engineering standards, delivery performance, and business outcomes.
• Translate business priorities into a sequenced roadmap for governed data products, semantic models, curated datasets, and reusable transformation frameworks.
• Establish scalable engineering practices that improve data quality, reliability, accessibility, adoption, and speed to insight.
• Align analytical engineering initiatives with Life & Retirement business priorities and enterprise data strategies.
• Serve as a strategic advisor to business and technology leadership regarding analytical engineering capabilities, investments, and opportunities.

Data Architecture & Engineering Excellence

• Provide architecture direction and technical quality oversight for high-impact analytical engineering solutions.
• Establish and maintain engineering standards for:
• Analytical data modeling and semantic layers
• Data quality, testing, and validation
• Documentation, governance, and maintainability
• Monitoring, observability, and production reliability
• Automation and continuous integration/continuous delivery (CI/CD)
• Reusable data transformations and scalable frameworks
• Guide the development of trusted, reusable analytical data products and governed metric definitions that support consistent reporting and decision-making.
• Provide oversight for scalable cloud-based data solutions, ensuring alignment with enterprise architecture, security, and governance requirements.
• Empower technical leads to own detailed solution design and hands-on execution while maintaining accountability for architecture standards and solution quality.

Portfolio Management & Delivery Performance

• Oversee analytical engineering initiatives from intake through development, implementation, adoption, and ongoing production support.
• Establish portfolio priorities, allocate capacity, and manage resources, dependencies, and risks across competing business initiatives.
• Define clear delivery commitments, quality expectations, and measures of success.
• Monitor portfolio performance and ensure analytical solutions deliver measurable business value.
• Reduce manual and duplicative reporting through reusable, governed, and well-supported analytical data products.
• Drive accountability for timely delivery, operational reliability, and continuous improvement.

Enterprise Partnership & Business Alignment

• Play a key leadership role in the development and implementation of Horace Mann's enterprise data warehouse, partnering with Enterprise Data and Technology teams to establish scalable architecture, data standards, and capabilities that support long-term analytical growth.
• Partner with Life & Retirement leadership, Analytics, Enterprise Data, Architecture, Security, Data Governance, and Technology to align divisional analytical engineering solutions with enterprise standards.
• Translate complex business requirements into scalable data strategies and engineering priorities.
• Influence cross-functional decisions related to data architecture, governance, quality, and analytical capabilities.
• Build strong relationships across business and technology teams to ensure solutions support operational needs and strategic objectives.
• Represent Life & Retirement analytical engineering priorities in enterprise data initiatives and planning discussions.

People Leadership & Talent Development

• Lead, coach, and develop analytical engineering professionals, building a high-performing team focused on technical excellence and business impact.
• Establish clear performance expectations, accountability, development plans, and succession strategies.
• Develop technical leaders and empower team members to take ownership of engineering solutions and delivery commitments.
• Foster a culture of collaboration, innovation, continuous learning, and operational excellence.
• Ensure team capabilities and resources evolve to meet changing business and technology needs.

Innovation & Continuous Improvement

• Champion modernization of analytical engineering practices, tools, and technologies.
• Identify opportunities to improve efficiency through automation, standardization, and reusable engineering frameworks.
• Evaluate emerging capabilities and recommend improvements that strengthen analytical delivery and business outcomes.
• Establish sustainable processes that improve engineering effectiveness, data product adoption, and long-term maintainability.

Qualifications & Experience

Required

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related quantitative field, or equivalent relevant professional experience.
• 8+ years of progressive experience in analytics engineering, data engineering, business intelligence, data modeling, or related disciplines.
• 3+ years of experience leading technical teams, technical leads, or a significant technical delivery portfolio.
• Demonstrated success building trusted, reusable analytical data products, governed metric and semantic layers, and scalable cloud-based data solutions.
• Advanced expertise in analytical engineering, data architecture, data modeling, and enterprise data product development.
• Proven ability to establish technical direction and oversee complex analytical engineering initiatives.
• Strong understanding of data governance, data quality, security, and enterprise architecture principles.
• Experience translating business priorities into technical roadmaps and measurable business outcomes.
• Demonstrated ability to lead organizational change, implement scalable engineering practices, and drive adoption of new capabilities.
• Strong strategic thinking, communication, collaboration, and decision-making skills.

Preferred

• Hands-on experience with modern analytical engineering technologies, including:
• Snowflake – Cloud-based data warehousing and analytical data solutions
• dbt or comparable transformation tools – Data transformation, modeling, testing, and documentation
• Power BI semantic models – Governed metrics, data modeling, and business intelligence
• SQL – Data querying, transformation, and analytical development
• Python – Data processing, automation, and engineering workflows
• CI/CD practices – Automated testing, deployment, and release management
• Experience in insurance, retirement, financial services, or another regulated industry.
• Master's degree, MBA, or advanced quantitative degree.

Key Skills & Competencies

• Strategic and technical leadership
• Analytical engineering and cloud data architecture
• People leadership and talent development
• Data product strategy and portfolio management
• Semantic modeling and governed metrics
• Snowflake, dbt, SQL, Python, and Power BI
• Engineering standards, automation, and CI/CD
• Data quality, governance, and reliability
• Resource planning and delivery accountability
• Cross-functional influence and stakeholder management
• Organizational change and continuous improvement
• Executive communication and business acumen

Additional Information

• Remote position.
• Periodic travel may be required.

Pay Range:

• $124,200.00 - $175,800.00 annually + bonus

Salary is commensurate to experience, location, etc.