Senior Data Architect - Digital Transformation Solutions at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

17 Feb, 26

Salary

0.0

Posted On

19 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architecture, AI, Semantic Modeling, Ontology Engineering, Graphs, Machine Learning Pipelines, Feature Stores, Model Metadata Management, Data Governance, Metadata Standards, GenAI, LLMs, Vector Databases, Data Engineering Tools, Communication Skills, Leadership Skills

Industry

Software Development

Description

- Design and maintain enterprise ontologies and semantic models to support AI and knowledge graph initiatives. - Collaborate with AI/ML teams to ensure data structures and pipelines support advanced analytics and model training. - Lead the data engineering strategy, including ingestion, transformation, and orchestration of structured and unstructured data. - Define and enforce data governance, metadata management, and data quality standards. - Partner with business stakeholders to translate strategic goals into data architecture requirements. - Evaluate and integrate emerging technologies in AI, semantic web, and data mesh architectures. - Mentor architects and engineers, fostering a culture of innovation and excellence. Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience. 8+ years of experience in data architecture. 3+ years focused on AI and semantic modeling. Experience in ontology engineering and graphs. Experience with machine learning pipelines, feature stores, and model metadata management. Familiarity with data governance frameworks and metadata standards. Experience with GenAI, LLMs, and vector databases. Familiarity with data governance frameworks and metadata standards (e.g., DCAT, schema.org). Proficient communication and leadership skills. Proficiency in data engineering tools (e.g., Azure Data Factory, Databricks, Spark, SQL). Contributions to open-source ontology or semantic web projects.

Responsibilities

Design and maintain enterprise ontologies and semantic models to support AI and knowledge graph initiatives. Lead the data engineering strategy, including ingestion, transformation, and orchestration of structured and unstructured data.