Senior Enterprise Data Architect

BOK Financial•Richardson, TX

10d•Onsite

About The Position

The AWS Data Architect is responsible for the strategy, design, and implementation of the company’s data infrastructure on Amazon Web Services (AWS). The role translates business outcomes into technical architecture, enables automation, and defines data integration patterns for different use cases. The architect leads the transition from the current data ecosystem to a target state, proposing and executing options that address short- and long-term business needs. The position also incorporates advanced AI architecture, including agentic AI, vector databases, Model Context Protocol (MCP), and Retrieval-Augmented Generation (RAG). The role works in a collaborative, fast-paced team where colleagues share expertise, support customers, and exchange ideas through weekly meetings, group huddles, and peer training. The position provides technical leadership and mentoring while supporting innovation across engineering teams. This position is based in an office. BOK Financial Corporation Group describes itself as financially stable and states that it provides employee training and development to support long-term careers. The companies in the group are equal opportunity employers.

Requirements

Bachelor’s degree in information systems, data analytics, or a related field.
15 or more years of experience in a data discipline, such as developing and implementing data frameworks, reference models, or operational and analytical data modeling.
Certification in TOGAF or a similar framework.

Responsibilities

Document current and target-state data architectures, including interim states and migration roadmaps, using AWS and other tools.
Present strategic execution options weighing business impact, cost, risk, and timelines.
Align data initiatives with business goals to deliver measurable outcomes, including improved customer experience and faster time-to-market.
Create and maintain reference architectures for batch, near-real-time, and real-time data flows from diverse sources.
Architect and implement scalable, low-latency data pipelines using Apache Kafka.
Integrate advanced AI architectures, including vector databases, MCP, and RAG, to enhance data processing and retrieval.
Promote automation and CI/CD practices, and establish patterns and reusable templates for rapid, consistent development.
Drive data governance and data quality by implementing best practices throughout the data lifecycle.
Provide leadership and technical guidance, mentor teams, and promote innovation.