Enterprise Data Architect

Empower Company S.R.O. • Greenwood Village, CO

2d

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. As an Enterprise Architect specializing in Machine Learning and Advanced Analytics, you will shape how Empower designs, delivers, and operates capabilities that help the business get the most from its data. This includes machine learning, analytics, and reporting that turns data into insights and decisions. You will define target architectures and roadmaps that make these capabilities easier to adopt and run reliably at scale, while contributing to the broader data strategy pillars including data architecture and infrastructure, data management, data security, data delivery, advanced analytics, and business alignment. You will partner across data engineering, data science, application engineering, security, risk, and business teams to establish clear direction, practical standards, reusable patterns, and measurable outcomes that improve speed to value, stability, compliance readiness, and cost control.

Requirements

• 15 years of deep hands-on experience delivering machine learning and advanced analytics solutions, with a strong understanding of how models are developed, evaluated, deployed, and supported in real business environments
• 7+ years of experience creating solution architectures and strategies across multiple architecture domains (business, application, data, integration, infrastructure and security)
• Demonstrated ability to set technical direction and drive adoption across teams through practical guidance, strong engineering judgment, and clear communication
• Proven experience working directly with data scientists and model developers, translating modeling needs into scalable, supportable, and secure implementation approaches
• 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 computer science or related field (information systems, mathematics, 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 capabilities
• Establish reference architectures, standards, and reusable patterns for data, analytics, and machine learning solutions that teams can adopt consistently
• Work closely 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 ensure machine learning solutions are designed 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
• Contribute to the broader data strategy pillars by shaping approaches to data architecture and infrastructure, data management, data security, data delivery, advanced analytics, and business alignment
• 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

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
• Number of Employees: 51-100 employees