Data Architect Resume

SUMMARY:

Experienced Professional as an Enterprise and Data Architect familiar with all phases of the system development life cycle, across multiple platforms and architectures with an emphasis on facilitating working sessions, gathering and analyzing business requirements, defining functional and technical specifications, and developing a Data Governance framework according to policies and best practices for managing data assets. These were positions requiring continuous interactions with top - level management, internal teams, and outside customers and clients in negotiating solutions with a history of producing results on-time and under budget.

TECHNICAL SKILLS

erwin, Tableau: , Power BI, SQL, Rational Enterprise Suite, Embarcadero E/R Studio, SPARX Enterprise Architect, XML, JSON, DOORS, Excel and other Microsoft Products, COBOL, others.

Frameworks: Zachman, TOGAF, FEAF, DoDAF. DMBOK

PROFESSIONAL EXPERIENCE:

Data Architect

Confidential

Evangelized and developed a framework for a Business-Driven approach defining a system agnostic Data Architecture. Proposed developing Enterprise Business Process Models and Data Models with common business semantics and supporting change control and governance processes. Established guidelines for reconciliation and mapping of legacy information.
Developed Data Model and Metadata Management standards to promote use of common data element concepts and reusable constructs. Provided guidelines for mentoring and coaching across directorates for data modeling to ensure compliance and generate the proper conceptual, logical and physical data models.
Discovered and captured information about core master data entities and relationships, and how they are utilized across business processes.
Managed lineage and provenance to link data specifications to their application implementation data touch points as part of the operationalization defining source systems and cataloging transformations of data to target systems assisting system integration and consolidation initiative.
Mapped and aligned data and process models and linked to metadata artifacts.

Data Architect

Confidential

Authored recommendations for modifications or extensions to the Aeronautical Information Exchange (AIXM) XML Schema’s core features in support of U.S. airspace requirements. Ensured requests synchronized with the AIXM UML Data Model . Proposals presented before a governance and review board.

Confidential

Data Architect

Co-authored Enterprise Data Architecture (EDA) Engagement model for the U.S. Census Bureau promoting discussion amongst system owners, key stakeholders and the enterprise data architecture team to define and enforce governance standards and ensure traceability between requirements, design and implementation to outline key drivers for maturing big data capabilities.
Extracted master data elements from the Enterprise Logical Data Model mapping data origination and lineage across the Census survey life cycle and monitored they aligned, conformed and were in compliance with Industry-standard Data Modeling methodologies and standards (e.g. National Information Exchange Model (NIEM), Confidential Enterprise Architecture Framework (FEAF)).
Certified data sources and information exchange interfaces (ESB, point-to-point) in a rapidly changing environment, synchronizing network topology in accordance with the Census Systems of Systems (SoS) approach and pushing information to an AWS Data Lake supporting business reporting requirements using SQL and Tableau.
Reversed engineered XSD, XML and JSON documenting legacy systems to support integration with new development adhering to the Data Architecture framework.

Confidential

Data Architect

Established an Enterprise Data Architecture Governance function instituting data modeling standards, naming standard compliance and information exchange standards assuring data quality.
Designed Enterprise data models by subject areas that considered Universal data models creating flexible structures allowing information from multiple applications to be synchronized and integrated within a single data construct resolving discrepancies between associated data dictionaries.
Developed Canonical Data Models presenting a common view to support Service Oriented Architecture (SOA) distinguishing critical data across subject areas for inclusion in a master file and provide a common point of reference.
Liaised with the business community to develop an Enterprise conceptual data model establishing a foundation for building out the Enterprise logical model.
Extended Enterprise Data Warehouse incorporating new business subject areas into an existing schema and development and refinement of dimensional data marts. Tasks included data profiling and cleansing, establishing Memorandums of Agreement and System Interface Agreements with external systems.

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