Data Architect
Company: Equifax, Inc.
Location: Alpharetta
Posted on: October 30, 2024
Job Description:
This role in the Global Data Office will report to the Head of
Enterprise Data Architecture, to specialize in four in-demand
areas: taxonomy development and management, graph schema design and
best practices, semantic "AI" techniques to prepare our data for
"AI" technologies and tools, and data governance and compliance. In
this role you will act as a subject matter expert that will be a
key contributor to enable Equifax to further leverage our
transformation into the cloud, to facilitate the creation of
advanced and differentiated offerings. Equifax has a hybrid work
schedule that allows for 2 days of remote work (Monday and Friday),
with 3 days onsite (Tuesday, Wednesday, Thursday) every week. This
role will work the required onsite days at our Equifax office in
Alpharetta, GA. Sponsorship is not available for this position.
This is a direct-hire role - not open to C2C or vendors. What
you'll do:
- Taxonomy Development and Management:
- Design and build domain specific taxonomies and
ontologies.
- 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.
- 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.
- 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.
- 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. What experience you need:
- 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.
- Familiarity with cloud and on-prem technologies, structured and
unstructured data, streaming and reposed data.
- 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.
- Knowledge of Python programming language.
- Experience with a data visualization and reporting tool.
- 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.
- Hands-on Technical capabilities such as - designing and
developing relational and non-relational data models.
- Excellent communication and collaboration skills, with proven
ability to work independently or as part of a team with strong
attention to detail. What could 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.
- 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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Keywords: Equifax, Inc., Johns Creek , Data Architect, Other , Alpharetta, Georgia
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