Director, Analytics Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Deliver strategic leadership and overall accountability for the analytical engineering operations within the Life & Retirement sector.

• Convert business objectives into actionable roadmaps for governed data products, semantic models, curated datasets, and reusable transformation frameworks.

• Develop scalable engineering practices aimed at enhancing data quality, reliability, accessibility, adoption, and speed to insight.

• Provide architectural guidance and maintain technical quality oversight for analytical engineering solutions.

• Set standards for data modeling, semantic layers, data quality, testing, validation, documentation, governance, monitoring, observability, reliability, automation, CI/CD, and reusable transformations.

• Oversee the creation of trustworthy analytical data products and governed metric definitions.

• Supervise scalable cloud-based data solutions that align with enterprise architecture, security, and governance requirements.

• Manage projects from the initial intake phase through development, implementation, adoption, and production support.

• Define portfolio priorities, allocate resources, and manage dependencies and risks effectively.

• Track portfolio performance and ensure that measurable business value is achieved.

• Lead the development and implementation of Horace Mann's enterprise data warehouse.

• Collaborate with Life & Retirement leadership, Analytics, Enterprise Data, Architecture, Security, Data Governance, and Technology teams.

• Interpret complex business requirements into scalable data strategies and engineering priorities.

• Mentor, coach, and develop professionals in analytical engineering.

• Set performance expectations, create development plans, and formulate succession strategies.

• Advocate for modernization, automation, standardization, reusable frameworks, and continuous improvement.

⛳️ Requirements

• A Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related quantitative field, or equivalent relevant professional experience.

• Over 8 years of progressive experience in analytics engineering, data engineering, business intelligence, data modeling, or related fields.

• More than 3 years of experience in leading technical teams, serving as a technical lead, or managing a substantial technical delivery portfolio.

• Proven track record in developing trusted, reusable analytical data products, governed metric and semantic layers, and scalable cloud-based data solutions.

• Advanced proficiency in analytical engineering, data architecture, data modeling, and enterprise data product development.

• Established capability to set technical direction and oversee complex analytical engineering projects.

• Strong grasp of data governance, data quality, security, and enterprise architecture principles.

• Experience in translating business priorities into technical roadmaps and measurable business results.

• Demonstrated ability to lead organizational change, adopt scalable engineering practices, and promote the utilization of new capabilities.

• Excellent strategic thinking, communication, collaboration, and decision-making abilities.

• Preferred: hands-on experience with Snowflake, dbt or similar transformation tools, Power BI semantic models, SQL, Python, and CI/CD practices.

• Preferred: experience in insurance, retirement, financial services, or another regulated industry.

• Preferred: Master's degree, MBA, or an advanced quantitative degree.

🏝️ Benefits

• Bonus opportunities.

• Flexibility of remote work.

• Occasional travel may be necessary.

• Special rates and benefits available for educators (company offering).