Senior Enterprise Architect - Data Architecture

If you’re passionate about building a better future for individuals, communities, and our country—and you’re committed to working hard to play your part in building that future—consider WGU as the next step in your career.

Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:
 

Pay Range: $175,900.00 - $272,600.00

Job Description

We are seeking a visionary and detail-oriented Sr Enterprise Architect - Data Architecture to lead the design and implementation of advanced data ecosystems in alignment with data mesh principles, big data processing, streaming technologies, modern data governance practices, and AI/ML/Generative AI. In this role, you will collaborate with stakeholders across the organization to create a scalable, decentralized, and secure data architecture that supports strategic decision-making, AI/ML innovation, and advanced analytics.

This is a critical role in defining the technical blueprint for how data is collected, processed, stored, shared, and governed across multiple domains while ensuring the architecture scales to meet future needs.

Key Responsibilities

Data Architecture Design and Strategy

• Develop and maintain a comprehensive enterprise data architecture that aligns with business goals, ensuring scalability, flexibility, and performance.

• Create data models, pipelines, and storage solutions optimized for structured, semi-structured, and unstructured data.

• Standardize data integration patterns, defining the technical stack and best practices for the organization.

Implementing Data Mesh Principles

• Lead the transition from a centralized data approach to a domain-driven, decentralized data mesh architecture.

• Define and promote the concept of data as a product, ensuring domain teams own and manage their data with self-serve capabilities.

• Design cross-domain data contracts to ensure interoperability and governance.

• Partner with engineering teams to implement domain-oriented data ownership and infrastructure.

Big Data and Streaming Solutions

• Architect and implement scalable big data platforms using tools like Hadoop, Snowflake, BigQuery, or Redshift.

• Design real-time data streaming and event-driven architectures using tools like Kafka, Apache Flink, or Apache Pulsar.

• Build systems to process and analyze large datasets efficiently, optimizing for latency and throughput.

• Integrate real-time and batch processing solutions to create unified data platforms.

AI/ML and Generative AI Enablement

• Design data infrastructure to support AI/ML and Generative AI initiatives, ensuring data pipelines deliver high-quality training data.

• Collaborate with data scientists to define and implement data architectures for machine learning workflows, including feature engineering and model deployment.

• Enable scalable experimentation and deployment of Generative AI models like GPT, Stable Diffusion, or domain-specific LLMs (Large Language Models).

• Develop strategies for model monitoring, data drift detection, and retraining pipelines.

Data Governance, Reporting, and Security

• Establish and implement data governance frameworks, policies, and standards that ensure security, compliance, and privacy across the organization.

• Deploy tools for data cataloging, metadata management, and lineage tracking (e.g., Collibra, Alation, Amundsen).

• Define and implement data quality management processes, including monitoring, profiling, and validation tools.

• Architect and implement data repor