APP DEV&TST - Data Architect - TechDigital
Lawrenceville, NJ
About the Job
Must Have List:
-Bachelor's degree in computer science, Life Science, Information Systems, Computer Engineering or equivalent is required by the EM.
-2+ years with data modeling or semantic data engineering
-4+ years with semantic data modeling tools such as Protégé, Centree or TopBraid.
-4+ years with data access languages such as SQL or SPARQL
Highly Preferred:
-Proficient with graph database such as neo4j, AnzoGraph or Amazon Neptune is highly preferred
-Proficient with programming languages such as Python, etc. is highly preferred.
Job Title: Ontologist/Semantic Data Architect
Job Location: Central New Jersey - Lawrenceville
Job Purpose:
Ontologist/Semantic Data Architect: This role involves FAIRification of data and is part of the FAIR Data Services team. This role is responsible for defining opportunities to standardize common business and scientific vocabularies, and to convert both legacy and new datasets into semantically enriched data assets.
Key Responsibilities:
As a member of the Semantic Data Engineering Team, you will support the translation of both legacy and new datasets into semantically enabled data models. Your responsibilities will include making Client research data more Findable, Accessible, Interoperable, and Reusable. Following the evaluation of existing business related process and data, development of semantic ontologies and taxonomies will be developed and used to both graph and harmonize research data. Opportunities to standardize existing vocabularies will be defined, and sematic vocabularies created. You will develop methods for providing access to these semantic data products through queries, APIs, and other programmatic means. In this role, you will collaborate with business partners, subject matter experts and engineering teams.
Educational Qualification: Bachelor's degree in Computer Science, Life Science, Information Systems, Computer Engineering or equivalent is preferred.
Technical/functional Skills:
· Experience working in a life sciences or biopharmaceutical environment such as early-stage research, drug discovery, or other biological sciences discipline is preferred.
· Familiarity with data engineering patterns and pipeline tools and processes including SQL vs NoSQL, GRAPHQL, SPARQL, ETL, Data Warehousing, Protégé, GraphQL, DataOps, TopBraid EDG, Centree, Termite.
· Able to present your work, both verbally and in writing, to diverse audiences including scientific stakeholders, technical teams, as well as research leadership.
· Able to effectively lead, manage, inspire, and influence globally distributed and cross-functional teams.
· Experience working in an agile software development environment
· Experience in representing and expressing information models (conceptual, logical, entities and their relationships), use of tools such as ER Studio to author such models.
· Experience in interpreting and translating Information models (conceptual and logical) to their equivalent semantic models (OWL, RDF etc.) using tools such as Top Braid, Protégé etc.
Experience:
· 5 years of experience with ontologies, taxonomies, RDF/OWL, SHACL, SPARQL, Knowledge Graphs, and related tools
· 3-5 years data architecture experience
· 3-5 years of experience in data quality management
· 3-5 years of experience in metadata management
· Experience with graph databases (neo4j, AnzoGraph, Amazon Neptune)
· Experience with taxonomy and ontology development tools and industry standard knowledge graph database tooling
· Experience in developing mappings and transformation processes to take data from a relational paradigm into a knowledge graph environment
· Experience utilizing graph data in a machine learning environment
· Working knowledge of databases, MDM, RDM, warehousing architecture, dimensional modelling, design patterns and strategy
· Experience collaborating with cross functional teams
· Must be proactive and self-driven, demonstrated initiative and be a logical thinker.
· Strong leadership, communication, collaboration skills with a track record of taking solution ownership
-Bachelor's degree in computer science, Life Science, Information Systems, Computer Engineering or equivalent is required by the EM.
-2+ years with data modeling or semantic data engineering
-4+ years with semantic data modeling tools such as Protégé, Centree or TopBraid.
-4+ years with data access languages such as SQL or SPARQL
Highly Preferred:
-Proficient with graph database such as neo4j, AnzoGraph or Amazon Neptune is highly preferred
-Proficient with programming languages such as Python, etc. is highly preferred.
Job Title: Ontologist/Semantic Data Architect
Job Location: Central New Jersey - Lawrenceville
Job Purpose:
Ontologist/Semantic Data Architect: This role involves FAIRification of data and is part of the FAIR Data Services team. This role is responsible for defining opportunities to standardize common business and scientific vocabularies, and to convert both legacy and new datasets into semantically enriched data assets.
Key Responsibilities:
As a member of the Semantic Data Engineering Team, you will support the translation of both legacy and new datasets into semantically enabled data models. Your responsibilities will include making Client research data more Findable, Accessible, Interoperable, and Reusable. Following the evaluation of existing business related process and data, development of semantic ontologies and taxonomies will be developed and used to both graph and harmonize research data. Opportunities to standardize existing vocabularies will be defined, and sematic vocabularies created. You will develop methods for providing access to these semantic data products through queries, APIs, and other programmatic means. In this role, you will collaborate with business partners, subject matter experts and engineering teams.
Educational Qualification: Bachelor's degree in Computer Science, Life Science, Information Systems, Computer Engineering or equivalent is preferred.
Technical/functional Skills:
· Experience working in a life sciences or biopharmaceutical environment such as early-stage research, drug discovery, or other biological sciences discipline is preferred.
· Familiarity with data engineering patterns and pipeline tools and processes including SQL vs NoSQL, GRAPHQL, SPARQL, ETL, Data Warehousing, Protégé, GraphQL, DataOps, TopBraid EDG, Centree, Termite.
· Able to present your work, both verbally and in writing, to diverse audiences including scientific stakeholders, technical teams, as well as research leadership.
· Able to effectively lead, manage, inspire, and influence globally distributed and cross-functional teams.
· Experience working in an agile software development environment
· Experience in representing and expressing information models (conceptual, logical, entities and their relationships), use of tools such as ER Studio to author such models.
· Experience in interpreting and translating Information models (conceptual and logical) to their equivalent semantic models (OWL, RDF etc.) using tools such as Top Braid, Protégé etc.
Experience:
· 5 years of experience with ontologies, taxonomies, RDF/OWL, SHACL, SPARQL, Knowledge Graphs, and related tools
· 3-5 years data architecture experience
· 3-5 years of experience in data quality management
· 3-5 years of experience in metadata management
· Experience with graph databases (neo4j, AnzoGraph, Amazon Neptune)
· Experience with taxonomy and ontology development tools and industry standard knowledge graph database tooling
· Experience in developing mappings and transformation processes to take data from a relational paradigm into a knowledge graph environment
· Experience utilizing graph data in a machine learning environment
· Working knowledge of databases, MDM, RDM, warehousing architecture, dimensional modelling, design patterns and strategy
· Experience collaborating with cross functional teams
· Must be proactive and self-driven, demonstrated initiative and be a logical thinker.
· Strong leadership, communication, collaboration skills with a track record of taking solution ownership
Source : TechDigital
