Lead Data Architect
On-site · Columbus, Ohio, United States
Job Summary
Lead Data Architect at Corporate Oversight and Governance Technology (COGT) guiding data architecture across multiple software applications on cloud platforms. Responsibilities include representing the data architecture team in governance bodies, evaluating technologies, designing and maintaining logical/physical data models (e.g., with Erwin), architecting scalable and secure data solutions, championing data mesh to enable decentralized ownership and self-serve data infrastructure, coordinating federated data sharing, delivering data product research and implementation, automating metadata management for discoverability and lineage, advising on database selection and storage design, guiding TDQ practices, enforcing secure data transfer between OLTP and data lakes, mentoring application development, data engineering, and governance teams, ensuring data quality, security, and regulatory compliance, and contributing to SDLC-wide data framework improvements. The role requires a Bachelor’s or Master’s degree, 5+ years in data architecture/engineering, experience with Erwin and Spark, strong communication, leadership, and the ability to drive innovative technologies.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field
- Formal training or certification in Data Architecture concepts
- 5+ years of applied experience in data architecture, data engineering, or a related discipline
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced proficiency in one or more programming languages, applications, and architecture
- Experience with data modeling tools (e.g., Erwin Data Modeler)
- Experience with big data processing frameworks (e.g., Spark)
- Experience with metadata management and automation tools is highly desirable
- Strong communication, collaboration, analytical and problem-solving abilities
- Ability to independently tackle complex design and functionality problems with little to no oversight
- Understanding of data mesh concepts and practical experience implementing data mesh methodologies
- Experience coordinating federated data sharing and data product development in large, complex enterprise environments
- Knowledge of data governance, data quality (including TDQ principles), and compliance best practices
- Ability to evaluate current and emerging technologies to select or recommend optimal solutions for future-state architecture
- Leadership in mentoring teams, establishing best practices, and driving adoption of innovative technologies
- Commitment to fostering a team culture of diversity, opportunity, inclusion, and respect
- Continuous learner, staying abreast of industry trends and emerging technologies
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