Semantic/AI Data Architect

2 days ago

Atlanta GA United States Ports North Full time

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 concepts.
    • Design and build taxonomies and ontologies that capture relationships between different entities and concepts.
    • Maintain and update taxonomies as business needs evolve.
    • Utilize 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 domain.
    • Work with database administrators and developers to ensure optimal performance and scalability of the graph database.
    • Design 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 models.
    • Develop and implement algorithms for semantic search, entity recognition, and relationship extraction.
    • Utilize 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 standards.
    • Participate in the development and implementation of data governance policies and procedures.
    • Work 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 use.
  • Support 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 purpose.
  • Work with IT to align underlying physical sources with the specified data architecture.
  • Support management of the data architecture through various governance processes.
  • Support the design and evolution of the architecture of our data asset to drive value and NPIs.
Skills Required
  • Familiarity with cloud and on-prem technologies, structured and unstructured data, streaming and repose data.
  • Experience designing data structures and solutions with a business's core infrastructure.
  • Experience with data modeling techniques and tools.
  • Experience in analytics and AI solutions such as NLP and ML.
  • Strong understanding of semantic web technologies, taxonomies, ontologies, and graph databases.
  • Proficiency in graph query languages: SPARQL, Cypher.
  • Knowledge of programming languages: Python, Java.
  • Experience with data visualization and reporting tools.
  • Understanding of financial services industry data and regulatory requirements.
  • Business Insight - Ability to understand the business use of the data in a given case, particularly the processes, decisions, and impacts that result from the data.
  • Business 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 cycles.
  • Collaboration - Skilled at leading meetings and creating collaboration (shared goals) among business and IT teams.
  • Technical 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 processes (agile, waterfall, etc.) - creating simplicity from complexity.
  • Technical 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 skills.
  • Excellent communication and collaboration skills.
  • Ability to translate complex technical concepts into business terms.
  • Ability to work independently and as part of a team.
  • Strong attention to detail and commitment to accuracy.
Education & Work Experience
  • BS degree in a STEM major or equivalent discipline; Master’s Degree strongly preferred.
  • 5-7 years of data analysis and modeling experience, particularly applied to common and specific business uses.
  • Cloud and other relevant technical certifications strongly preferred.
What 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 use.
  • Domain 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.
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