Technical Data Architect Sr

Doosan Corp•Minneapolis, MN

21d

About The Position

At Doosan Bobcat, our success is powered by our people. Through our winning culture and one global team working together, we deliver the best products and service to our customers – and make the world a better place. Join our team today and start building your career with a worldwide leader. Job InformationThe Senior Data Architect is responsible for designing, optimizing, and governing the organization’s enterprise data architecture to enable advanced analytics and AI-driven solutions. This role leads the development of scalable, secure, and cloud-native data ecosystems, ensuring data is AI-ready and governed to the highest standards.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
10+ years of experience in data architecture, software development, and technical leadership.
Proven expertise in physical data modeling, NoSQL/distributed databases, scalable ETL frameworks, and cloud-native architectures.
Experience establishing data governance policies and designing secure, high-availability data systems.
Hands-on experience with AI/ML data pipelines, automated feature engineering, and generative AI data infrastructure (vector databases, embeddings). Expectation for this role is to be hands-on 20-30% of their time.
Strong leadership, mentoring, and communication skills with a track record of influencing cross-functional teams.

Nice To Haves

Experience with open-source analytical technologies (R, Python, TensorFlow) and BI tools (Power BI).
Experience with Snowflake and dbt preferred.
Agile development experience.
Ability to balance immediate business needs with long-term strategic data architecture goals.

Responsibilities

Governance Framework: Establish and enforce enterprise-wide governance policies, ensuring data lineage, cataloguing, and stewardship are embedded in the development lifecycle.
Data Quality: Oversee the strategy for Bobcat’s data quality framework establishing trustworthiness for critical business entities.
Security & Privacy: Collaborate with Risk Management to design architectures that adhere to regulations such as GDPR/CCPA, internal compliance standards, and role-based access controls (RBAC).
Enterprise Data Modelling: Own the conceptual and logical data models to support business analytics and AI initiatives.
Information Architecture: Collaborate with Bobcat knowledge workers to build an information architectural roadmap to enable the secure ingestion, synthesis, tagging and dispensation of structured and unstructured data that can be utilized to solve complex business problems for both internal and external personas.
Ontology: Define the vision, structure, and adoption plan for Bobcat’s ontology so AI systems can operate with consistent meaning, context, and reasoning
AI Center of Excellence (AI COE) Collaboration: Collaborate with Bobcat's AI COE to align Data Architectural Roadmaps with Targeted Business Outcomes. Ensure the architecture enables scalable environments for data analysis and development of Large Language Models.
AI-Ready Infrastructure: Design the data foundation required for MLOps, ensuring seamless data provisioning for training, testing, and deploying machine learning models.
GenAI & Semantic Layer: Architect the storage and retrieval strategies for Generative AI, including Vector Databases, Knowledge Graphs, and embeddings to support RAG (Retrieval-Augmented Generation).
Strategic Alignment: Translate complex technical concepts into business value proposition for C-level executives and non-technical stakeholders.
Technical Leadership: Partner with Bobcat’s Enterprise and Solution Architects to drive alignment across Business, Data, Application, and Technical Architecture at the Enterprise level. Mentor data engineers and junior architects, conducting reviews to ensure alignment with architectural standards.
Vendor Management: Evaluate third-party tools and vendors to build a build-vs-buy strategy that fits Bobcat’s ecosystem.