Job description

Our Company Explore how you can contribute at AmeriLife. For over 50 years, AmeriLife has been a leader in the development, marketing and distribution of annuity, life and health insurance solutions for those planning for and living in retirement. Associates get satisfaction from knowing they provide agents, marketers and carrier partners the support needed to succeed in a rapidly evolving industry. Job Summary The Senior Data Architect is a senior technical leader responsible for defining, designing, and governing AmeriLife’s enterprise data architecture across modern cloud platforms. This role leads the design of scalable, secure, and high-performing data platforms, enterprise data models, semantic models, and data products that enable analytics, AI, governance, regulatory reporting, and enterprise decision making. The ideal candidate is a highly hands-on architect with deep expertise in Databricks, enterprise data modeling, advanced SQL, cloud data platforms, Data Vault 2.0, metadata management, and enterprise architecture. This individual partners closely with engineering, analytics, governance, and business teams while actively designing and implementing enterprise-scale data solutions. Job Description Key Responsibilities Lead the architecture and design of enterprise data platforms, enterprise data products, and modern lakehouse solutions. Define and maintain enterprise conceptual, logical, and physical data models across business domains. Design canonical data models, semantic models, dimensional models, Data Vault 2.0 models, and normalized data models to support operational and analytical workloads. Establish enterprise data modeling standards, naming conventions, modeling best practices, and architecture governance. Design scalable data solutions using Databricks Lakehouse, Delta Lake, Unity Catalog, and modern cloud technologies. Develop and optimize complex SQL solutions for large-scale analytical workloads, data transformations, data quality validation, and performance optimization. Partner with Data Engineering teams to ensure architecture standards and enterprise data models are consistently implemented. Lead architecture reviews, solution design sessions, and technical governance across enterprise initiatives. Design metadata-driven frameworks, reusable architecture patterns, and standardized data pipelines. Partner with Data Governance teams on metadata, lineage, stewardship, business glossary, master data management (MDM), and data quality. Optimize platform scalability, performance, reliability, security, and cost efficiency. Mentor architects and engineers on enterprise architecture, data modeling, SQL optimization, and engineering best practices. Evaluate emerging technologies and recommend future-state architecture aligned with enterprise strategy. Required Qualifications Bachelor s degree in computer science, Information Systems, Engineering, or a related field. Master’s degree preferred. 10 years of experience in enterprise data architecture and enterprise data modeling. 5 years of experience designing cloud-native data platforms and modern data architectures. Expert-level SQL skills, including query optimization, execution plan analysis, indexing strategies, window functions, stored procedures, complex joins, and performance tuning. Strong hands-on experience with the Databricks Lakehouse Platform. Deep expertise in conceptual, logical, physical, dimensional, semantic, and Data Vault 2.0 data modeling. Extensive experience with enterprise data modeling tools such as Erwin Data Modeler, ER/Studio, Lucidchart, Visio, or equivalent platforms. Strong experience with Apache Spark, Delta Lake, Unity Catalog, Python, and SQL. Experience designing enterprise data warehouses, lakehouses, semantic layers, and enterprise data products. Strong knowledge of Azure cloud services including Azure Data Lake Storage, Azure Data Factory, Microsoft Entra ID, Azure Functions, and related services. Experience implementing CI/CD, Infrastructure as Code, Git, and DevOps best practices. Strong understanding of metadata management, lineage, governance, master data management (MDM), reference data management, and data quality. Excellent analytical, communication, and stakeholder management skills. Preferred Qualifications Microsoft Azure Solutions Architect Expert or equivalent certifications. Databricks Certified Data Engineer Professional or equivalent certification. Experience implementing enterprise metadata repositories and data catalogs. Experience with Snowflake Secure Data Sharing. Experience supporting AI, machine learning, and enterprise analytics platforms. Experience within financial services, insurance, or other highly regulated industries. Technical Skills Enterprise Data Architecture Enterprise Data Modeling Conceptual, Logical, Physical Data Modeling Data Vault 2.0 Dimensional Modeling Semantic Layer Modeling Canonical Data Modeling Databricks Lakehouse Delta Lake Unity Catalog Apache Spark Expert SQL SQL Performance Tuning Python Azure Data Lake Storage Azure Data Factory Microsoft Entra ID Data Modeling Tools (Erwin, ER/Studio, Visio) Metadata Management Data Governance Master Data Management (MDM) Reference Data Management (RDM) Data Quality Performance Optimization Leadership Competencies Enterprise architecture leadership Technical thought leadership Data modeling expertise Solution architecture Technical mentoring Cross-functional collaboration Executive communication Strategic problem solving Innovation mindset Compensation Salary Range: $165,000 to $170,000 This role may be eligible for a discretionary annual bonus. Salary offers will vary commensurate with experience, education, skills, and training What AmeriLife Offers A comprehensive benefits package that includes PTO, medical, dental, vision, retirement savings, disability insurance, and life insurance. Equal Employment Opportunity Statement We are an Equal Opportunity Employer and value diversity at all levels of the organization. All employment decisions are made without regard to race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity or expression, age, national origin, ancestry, disability, genetic information, marital status, veteran or military status, or any other protected characteristic under applicable federal, state, or local law. We are committed to providing an inclusive, equitable, and respectful workplace where all employees can thrive. Americans with Disabilities Act (ADA) Statement We are committed to full compliance with the Americans with Disabilities Act (ADA) and all applicable state and local disability laws. Reasonable accommodations are available to qualified applicants and employees with disabilities throughout the application and employment process. Requests for accommodation will be handled confidentially. If you require assistance or accommodation during the application process, please contact us at HR AmeriLife.com . Pay Transparency Statement We are committed to pay transparency and equity, in accordance with applicable federal, state, and local laws. Compensation for this role will be determined based on skills, qualifications, experience, and market factors. Where required by law, the pay range for this position will be disclosed in the job posting or provided upon request. Additional compensation information, such as benefits, bonuses, and commissions, will be provided as required by law. We do not discriminate or retaliate against employees or applicants for inquiring about, discussing, or disclosing their pay or the pay of another employee or applicant, as protected under applicable law. Pay ranges are available upon request. Background Screening Statement Employment offers are contingent upon the successful completion of a background screening, which may include employment verification, education verification, criminal history check, and other job-related inquiries, as permitted by law. All screenings are conducted in accordance with applicable federal, state, and local laws, and information collected will be kept confidential. If any adverse decision is made based on the results, applicants will be notified and given an opportunity to respond.

Requirements

Must-haves

Explore how you can contribute at AmeriLife.
Associates get satisfaction from knowing they provide agents, marketers and carrier partners the support needed to succeed in a rapidly evolving industry.
Lead the architecture and design of enterprise data platforms, enterprise data products, and modern lakehouse solutions.
Define and maintain enterprise conceptual, logical, and physical data models across business domains.
Design canonical data models, semantic models, dimensional models, Data Vault 2.0 models, and normalized data models to support operational and analytical workloads.
Establish enterprise data modeling standards, naming conventions, modeling best practices, and architecture governance.
Design scalable data solutions using Databricks Lakehouse, Delta Lake, Unity Catalog, and modern cloud technologies.
Develop and optimize complex SQL solutions for large-scale analytical workloads, data transformations, data quality validation, and performance optimization.
Partner with Data Engineering teams to ensure architecture standards and enterprise data models are consistently implemented.
Lead architecture reviews, solution design sessions, and technical governance across enterprise initiatives.
Design metadata-driven frameworks, reusable architecture patterns, and standardized data pipelines.
Partner with Data Governance teams on metadata, lineage, stewardship, business glossary, master data management (MDM), and data quality.

Nice-to-haves

Bachelor s degree in computer science, Information Systems, Engineering, or a related field. Master’s degree preferred.
Microsoft Azure Solutions Architect Expert or equivalent certifications.
Databricks Certified Data Engineer Professional or equivalent certification.
Experience implementing enterprise metadata repositories and data catalogs.
Experience with Snowflake Secure Data Sharing.
Experience supporting AI, machine learning, and enterprise analytics platforms.
Experience within financial services, insurance, or other highly regulated industries.
Technical Skills
Enterprise Data Architecture
Enterprise Data Modeling
Conceptual, Logical, Physical Data Modeling
Data Vault 2.0

Application prep

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Keywords to mirror

aisqlpythonazureci/cdmachine learning

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

Pto