Note: The job is a remote job and is open to candidates in USA. Southern Glazer's Wine and Spirits LLC is seeking a Senior Unified Data Semantic Engineer. The role involves designing and developing a scalable semantic layer framework integrated with AI and ML components, while ensuring alignment with industry standards and providing support to engineering and business teams.
Responsibilities
- Design and develop a scalable modular semantic layer framework that can be seamlessly integrated with various data and artificial intelligence (AI) and machine learning (ML) components across the organization
- Ensure the semantic layer is aligned with industry standards and best practices for knowledge representation, such as RDF, OWL, and SPARQL
- Develop the necessary frameworks and interfaces to enable the integration of the semantic layer into various AI/ML use cases
- Establish the governance processes and mechanisms to maintain the integrity, consistency, and accuracy of the semantic layer over time
- Provide training and support to the wider engineering and business teams to facilitate the adoption and effective utilization of the semantic layer
- Continuously monitor and enhance the semantic layer to address evolving business requirements and technological advances
- Collaborate with the enterprise architecture, data architecture, and AI/ML teams to ensure the semantic layer is aligned with the organization's overall data and technology strategy
- May telecommute but must reside near Miramar, Florida headquarters or Dallas, Texas office
- Requires up to 10% domestic travel
Skills
- Master's degree (or foreign equivalent) in computer science or related field; plus 3 years of experience in job offered or similar occupation
- Bachelor's degree plus 5 years of experience also acceptable
- At least 3 years of experience in framework development and building semantic layers to solve complex business use cases
- Knowledge of data engineering, computer programming (Python, Scala, or Java), and AI/ML algorithms
- Experience with large-scale datasets and developing semantic layer solutions (Databricks, Snowflake, or similar) and cloud-based data warehousing and transformation tools (Delta Lake tables, DBT, Fivetran, or similar)
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