Infinity Consulting Solutions
Semantic/AI Data Architect
Infinity Consulting Solutions, Atlanta, Georgia, United States, 30383
Title: Semantic/AI Data Architect
Location: Hybrid in Atlanta or Alpharetta, GA (2 days WFH)
Client Industry: Financial Services
Compensation: $60-$82/Hr (Contract-to-hire)
We have partnered with our client in their search for a
Semantic/AI Data Architect.
This role will be pivotal in aligning the data architecture with enterprise strategy. The role demands expertise in taxonomy, ontology development, graph schema design, and semantic AI to enhance data processing and governance. By enabling insights through advanced AI methodologies and rigorous data standards, the architect will empower business teams to harness accurate and compliant data resources. Additionally, the position requires a proactive approach in balancing technical, compliance, and business requirements to drive both innovation and reliability in data management practices.Responsibilities
Taxonomy Development and Management
Collaborate with business users to understand their domain-specific terminology and conceptsDesign and build taxonomies and ontologies that capture relationships between different entities and conceptsMaintain and update taxonomies as business needs evolveUtilize taxonomies to improve search, information retrieval, and knowledge management
Graph Schema Design and Implementation
Develop and implement graph data models that accurately represent the complex relationships between entities in the financial domainWork with database administrators and developers to ensure optimal performance and scalability of the graph databaseDesign and develop queries and algorithms to extract insights from the graph data
Semantic AI Integration
Leverage AI technologies such as natural language processing (NLP) and machine learning (ML) to enhance the capabilities of taxonomies and graph data modelsDevelop and implement algorithms for semantic search, entity recognition, and relationship extractionUtilize semantic AI to improve the accuracy and efficiency of data analysis and decision-making processes
Data Governance and Compliance
Ensure that data models, taxonomies, and AI applications adhere to regulatory requirements and industry standardsParticipate in the development and implementation of data governance policies and proceduresWork with legal and compliance teams to ensure that data is used ethically and responsibly
Support the design and implementation of data models that enable the acquisition, production, storage, access, analysis, and delivery of data to meet business objectives, acting as a bridge between the data requirements of business and analytic processes, and the physical implementation of that data in technology infrastructure.Align components of the data environment with the enterprise data strategy - by understanding data structures and flows and how they relate to business useSupport the identification of taxonomies, metadata requirements, and other standards that are critical to ensuring that the meaning of data is precise and unambiguous, and that data is accessible and aligned with business purposeWork with IT to align underlying physical sources with the specified data architectureSupport management of the data architecture through various governance processesSupport the design and evolution of the architecture of our data asset to drive value and NPIsSkills Required
Familiarity with cloud and on prem technologies, structured and unstructured data, streaming and reposed dataExperience designing data structures and solutions with a business's core infrastructureExperience with data modeling techniques and toolsExperience in analytics and AI solutions such as NLP and MLStrong understanding of semantic web technologies, taxonomies, ontologies, and graph databasesProficiency in graph query languages: SPARQL, CypherKnowledge of programming languages: Python, JavaExperience with data visualization and reporting toolsUnderstanding of financial services industry data and regulatory requirementsBusiness Insight - Ability to understand the business use of the data in a given case, particularly the processes, decisions, and impacts that result from the dataBusiness Partnership and Consulting - Experience working closely with business and analytics teams to understand their needs (e.g., design thinking sessions, business requirements, agile methods, etc.), maintain ongoing engagement through development, rollout, and improvement cyclesCollaboration - Skilled at leading meetings and creating collaboration (shared goals) among business and IT teamsTechnical Communication / Presentation - Experience translating business requirements into technical requirements for IT and vice versa, through both written and verbal channels at a variety of points in different SDLC process (agile, waterfall, etc.) - creating simplicity from complexityTechnical Knowledge - Experience designing and developing relational and non-relational data models in a variety of database technologies (GCP, Oracle, Microsoft, etc.)Soft Skills
Strong analytical and problem-solving skillsExcellent communication and collaboration skillsAbility to translate complex technical concepts into business termsAbility to work independently and as part of a teamStrong attention to detail and commitment to accuracy
Education& Work
Experience
BS degree in a STEM major or equivalent discipline; Master's Degree strongly preferred5-7 years of data analysis and modeling experience, particularly applied to common and specific business usesCloud and other relevant technical certifications strongly preferredWhat Will Set You Apart
Technical Advising / Consulting - Experience modeling entities, relationships, attributes, and abstract data building blocks for a given business case, considering both specific database / physical design as well as the logical and conceptual design required for business useDomain Knowledge: A solid understanding of financial products, markets, and regulations is crucial for effective communication and collaboration with business stakeholders.Data Security and Privacy: The financial services industry is subject to strict data security and privacy regulations. A data architect must be well-versed in these regulations and ensure that their work adheres to them.Risk Management: Understanding of risk management principles and how data can be used to identify and mitigate risks is important in the financial sector.
Location: Hybrid in Atlanta or Alpharetta, GA (2 days WFH)
Client Industry: Financial Services
Compensation: $60-$82/Hr (Contract-to-hire)
We have partnered with our client in their search for a
Semantic/AI Data Architect.
This role will be pivotal in aligning the data architecture with enterprise strategy. The role demands expertise in taxonomy, ontology development, graph schema design, and semantic AI to enhance data processing and governance. By enabling insights through advanced AI methodologies and rigorous data standards, the architect will empower business teams to harness accurate and compliant data resources. Additionally, the position requires a proactive approach in balancing technical, compliance, and business requirements to drive both innovation and reliability in data management practices.Responsibilities
Taxonomy Development and Management
Collaborate with business users to understand their domain-specific terminology and conceptsDesign and build taxonomies and ontologies that capture relationships between different entities and conceptsMaintain and update taxonomies as business needs evolveUtilize taxonomies to improve search, information retrieval, and knowledge management
Graph Schema Design and Implementation
Develop and implement graph data models that accurately represent the complex relationships between entities in the financial domainWork with database administrators and developers to ensure optimal performance and scalability of the graph databaseDesign and develop queries and algorithms to extract insights from the graph data
Semantic AI Integration
Leverage AI technologies such as natural language processing (NLP) and machine learning (ML) to enhance the capabilities of taxonomies and graph data modelsDevelop and implement algorithms for semantic search, entity recognition, and relationship extractionUtilize semantic AI to improve the accuracy and efficiency of data analysis and decision-making processes
Data Governance and Compliance
Ensure that data models, taxonomies, and AI applications adhere to regulatory requirements and industry standardsParticipate in the development and implementation of data governance policies and proceduresWork with legal and compliance teams to ensure that data is used ethically and responsibly
Support the design and implementation of data models that enable the acquisition, production, storage, access, analysis, and delivery of data to meet business objectives, acting as a bridge between the data requirements of business and analytic processes, and the physical implementation of that data in technology infrastructure.Align components of the data environment with the enterprise data strategy - by understanding data structures and flows and how they relate to business useSupport the identification of taxonomies, metadata requirements, and other standards that are critical to ensuring that the meaning of data is precise and unambiguous, and that data is accessible and aligned with business purposeWork with IT to align underlying physical sources with the specified data architectureSupport management of the data architecture through various governance processesSupport the design and evolution of the architecture of our data asset to drive value and NPIsSkills Required
Familiarity with cloud and on prem technologies, structured and unstructured data, streaming and reposed dataExperience designing data structures and solutions with a business's core infrastructureExperience with data modeling techniques and toolsExperience in analytics and AI solutions such as NLP and MLStrong understanding of semantic web technologies, taxonomies, ontologies, and graph databasesProficiency in graph query languages: SPARQL, CypherKnowledge of programming languages: Python, JavaExperience with data visualization and reporting toolsUnderstanding of financial services industry data and regulatory requirementsBusiness Insight - Ability to understand the business use of the data in a given case, particularly the processes, decisions, and impacts that result from the dataBusiness Partnership and Consulting - Experience working closely with business and analytics teams to understand their needs (e.g., design thinking sessions, business requirements, agile methods, etc.), maintain ongoing engagement through development, rollout, and improvement cyclesCollaboration - Skilled at leading meetings and creating collaboration (shared goals) among business and IT teamsTechnical Communication / Presentation - Experience translating business requirements into technical requirements for IT and vice versa, through both written and verbal channels at a variety of points in different SDLC process (agile, waterfall, etc.) - creating simplicity from complexityTechnical Knowledge - Experience designing and developing relational and non-relational data models in a variety of database technologies (GCP, Oracle, Microsoft, etc.)Soft Skills
Strong analytical and problem-solving skillsExcellent communication and collaboration skillsAbility to translate complex technical concepts into business termsAbility to work independently and as part of a teamStrong attention to detail and commitment to accuracy
Education& Work
Experience
BS degree in a STEM major or equivalent discipline; Master's Degree strongly preferred5-7 years of data analysis and modeling experience, particularly applied to common and specific business usesCloud and other relevant technical certifications strongly preferredWhat Will Set You Apart
Technical Advising / Consulting - Experience modeling entities, relationships, attributes, and abstract data building blocks for a given business case, considering both specific database / physical design as well as the logical and conceptual design required for business useDomain Knowledge: A solid understanding of financial products, markets, and regulations is crucial for effective communication and collaboration with business stakeholders.Data Security and Privacy: The financial services industry is subject to strict data security and privacy regulations. A data architect must be well-versed in these regulations and ensure that their work adheres to them.Risk Management: Understanding of risk management principles and how data can be used to identify and mitigate risks is important in the financial sector.