Enterprise Data Architect

Empower • Overland Park, KS

1d • Remote

About The Position

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them. Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT. The Enterprise Architect will shape how Empower designs, delivers, and operates data science, machine learning, advanced analytics, business intelligence, and data delivery capabilities so the business can get more value from its data. This role will define target architectures and roadmaps that make analytics and ML easier to adopt and run reliably at scale, establish practical standards and reusable patterns, and partner across data engineering, data science, application engineering, security, risk, and business teams to improve speed to value, stability, compliance readiness, and cost control.

Requirements

• 15+ years of experience in solution development and delivery, including deep hands-on delivery of machine learning and advanced analytics solutions with direct involvement in data science and modeling work such as feature engineering, model selection, training, and evaluation in real business environments.
• 7+ years of architecture experience, including defining and maintaining enterprise target architectures and roadmaps, and establishing reference architectures, standards, and reusable patterns that teams adopt consistently.
• Working knowledge of common data science practices, including problem framing, experimentation, metric definition, and communicating model performance and limitations to technical and non-technical audiences.
• Proven experience working directly with data scientists and model developers, translating modeling needs into scalable, supportable, and secure implementation approaches.
• Demonstrated ability to set technical direction and drive adoption across teams through practical guidance, strong engineering judgment, and clear communication.
• Hands-on experience with at least one modern analytics or machine learning platform such as Snowflake, Databricks, SAS, Amazon SageMaker, Dataiku, or equivalent.
• Cloud experience designing or deploying data and analytics solutions on a major cloud platform, with understanding of scalability, reliability, security, and cost considerations.
• Strong understanding of modern data concepts including pipelines, data modeling, data quality practices, metadata, and consumption patterns for analytics and ML.
• Ability to partner effectively across engineering, data science, security, risk, and business stakeholders and drive outcomes through influence and collaboration.
• Strong written and verbal communication skills with demonstrated ability to create clear technical direction and documentation that teams will use.
• Bachelor’s and/or master’s degree in data science or related field (computer science, information systems, mathematics, statistics, software engineering, etc.).

Nice To Haves

• Experience in financial services, wealth management, retirement services, or another regulated industry.
• Experience setting enterprise-wide patterns or standards for ML, analytics, or data platforms.
• Experience with more than one modern analytics or machine learning platform.
• Familiarity with controls relevant to data, analytics, and ML including privacy, access management, auditability, and operational accountability.
• Relevant cloud certifications or formal training in cloud architecture, data engineering, analytics, or machine learning.

Responsibilities

• Define and maintain enterprise target architectures and roadmaps for advanced analytics, machine learning, business intelligence, and data delivery capabilities.
• Establish reference architectures, standards, and reusable patterns for data, analytics, and machine learning solutions that teams can adopt consistently.
• Partner with data scientists and model developers to translate modeling approaches into production-ready designs, ensuring smooth paths from experimentation to operational use.
• Partner with data science and engineering teams to design machine learning solutions for production use, including scalability, reliability, monitoring, and maintainability.
• Provide architectural direction for analytics and reporting capabilities, including how curated data sets, semantic layers, and consumption patterns support consistent business metrics and insights.
• Provide leadership for data platforms and pipelines, including guidance on integration patterns, reusable components, automation, and operational resilience.
• Collaborate with security, privacy, and risk stakeholders to ensure data and analytics solutions incorporate appropriate controls, traceability, and compliance readiness.
• Lead architecture reviews and decision forums, ensuring decisions are documented and aligned to enterprise direction.
• Define success measures for data and analytics adoption, including delivery efficiency, reliability, reusability, quality, and value realized.
• Drive simplification and modernization by reducing duplicated tooling and inconsistent practices across data, analytics, and machine learning solutions.
• Support pilots and early adopters by converting lessons learned into scalable enterprise guidance and repeatable patterns.
• Influence stakeholders to improve outcomes such as faster time to insight, faster delivery of trusted analytics, more reliable production ML usage, and improved cost transparency for data and analytics workloads.
• Contribute to broader data strategy pillars by shaping approaches to data architecture and infrastructure, data management, data security, data delivery, advanced analytics, and business alignment.

Benefits

• Medical, dental, vision and life insurance
• Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
• Tuition reimbursement up to $5,250/year
• Business-casual environment that includes the option to wear jeans
• Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
• Paid volunteer time — 16 hours per calendar year
• Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
• Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level