Architect of Data Architecture

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 Data Architect will serve as a hands-on technical expert and solution architecture contributor, helping design Empower’s cloud and data architecture. This role will partner with enterprise architects, senior architects, business leaders, IT teams, and Empower’s Innovation Lab to shape solution architectures, support modernization initiatives, explore emerging technologies including Generative AI and Advanced Analytics, and translate experimentation into practical patterns and recommendations for delivery teams.

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  Partner with Enterprise Architects, Senior Architects, and cross functional teams, including business stakeholders, to shape solution architectures aligned to a unified IT data strategy.

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  Contribute to Empower’s technology roadmap by documenting target state architectures, reference architectures, and key dependencies for supported initiatives.

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  Design and support modernization and migration of complex systems to scalable, secure, and cost optimized cloud architectures, working with delivery teams through implementation.

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  Evaluate and prototype new technologies and applications, challenge existing approaches constructively, and provide input into business cases and recommendations.

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  Apply and help operationalize architectural standards, best practices, and governance expectations, supporting consistent adoption through guidance and enablement.

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  Collaborate closely with business and engineering teams to design end to end solutions that meet strategic, technical, and operational objectives.

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  Provide architectural guidance in process design, system orchestration, and enterprise integration to enable cohesive and efficient technology ecosystems.

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  Champion security, resilience, and scalability as core design principles across data platforms and data solutions.

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  Contribute to architecture discipline maturity by producing reusable patterns, decision documentation, and lessons learned that improve consistency and delivery speed.

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  Support full stack development teams through solution design and implementation, improving long term scalability, performance, and cost outcomes.

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  Data engineering experience designing and delivering ETL and ELT pipelines, including orchestration, data quality controls, and reliable operations for batch and near real time workloads.

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  Streaming and event driven data experience building and operating Kafka or Kinesis based architectures, including ordering, replay, schema evolution, and real time observability.

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  API and integration experience designing API first data access patterns, API lifecycle governance, versioning, security, and developer enablement, plus event driven integration patterns to reduce point to point complexity.

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  Data platform modernization experience designing large scale ingestion and processing platforms using Spark or comparable distributed compute and orchestrating reliable batch and near real time pipelines.

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  Data security and privacy experience implementing encryption, masking or tokenization, access controls, and auditability patterns for sensitive data and regulated environments.

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  Cloud cost and performance experience applying FinOps practices, workload right sizing, storage optimization, and performance engineering for cloud data platforms.

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  DevOps for data experience building CI/CD for data pipelines, infrastructure as code practices, and container platforms such as Kubernetes or EKS for data workloads.

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  Applied AI and GenAI experience designing safe enterprise patterns for retrieval, evaluation, monitoring, and responsible AI adoption.

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  Broad polyglot engineering experience with Java, microservices patterns, and third party API integrations that support data intensive services.

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  Certifications such as AWS Certified Solutions Architect, Associate or Professional.

This job operates in a professional office environment.

This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job. The employer has the right to revise this job description at any time. You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description. You may be required to perform other duties that are not included on this job description. The job description is not a contract for employment, and either you or the employer may terminate employment at any time, for any reason, as per terms and conditions of your employment contract.