SUMMARY:

• An experienced and dedicated DATA ARCHITECT with an established history of providing business insights and enabling data - driven decision-making to support strategic initiatives
• Documented career path as a critical team member leading the development and innovation of data strategy and architectural frameworks
• Served as a liaison between business data consumers and the data warehouse/BI teams
• Engaged organizations to understand their data needs, how they access and analyze data and the processes and systems used to interact with data
• Defined standards for managing, modeling, and delivering data within the enterprise
• Partnered with and engaged members of the divisional business leadership, Enterprise Risk Management, Data Warehouse, and business process teams to understand the business requirements and generate the best designs for the solution architectures
• Drove the implementation and adoption of new data architecture solutions with key stakeholders and core business teams
• Provided direction to data engineers on the implementation of relational and dimensional model
• Developed and validated modeling solutions
• Integrated and drove modeling solutions into existing business processes
• Maintained data models and standards documentation on master data

SKILL:

• Database Development Oracle Data Warehousing Management and Development
• 30 plus years of IT experience data management and data modeling primarily in dimensional modeling in private and government sector
• Excellent problem solving and strong communication skills formed from lifetime of involvement in quantitative science and economic and financial activities
• Identified the current-and-future-state business processes and helping the business stakeholders envision the future
• Possesses strong analytical and communication skills and superb writing abilities
• Analyzed business requirements, designing/modifying system processes to meet the analytical capability needs and communicating them to the rest of the application development a data warehouse team through the practical adoption of industry best practices, data design patterns and modeling techniques
• Proven working experience as a data modeler/data architect
• Well versed with data warehousing concepts and its design by using star and snowflake schema methodologies as well as an understanding of the Data Vault (DW 2.0) and Ontologies and Semantic Models
• Technical expertise regarding data models, database design development, data mining and segmentation techniques
• Experienced in data modelling and application design and development offering a rich mixture of business and technical expertise in data warehousing and reporting
• Evaluated existing data models and physical databases for variances and discrepancies using automated and visual techniques along with programmatic analysis
• Responsible for preparation of source to target mappings through an integrated, streamlined and productive paring of a variety of industry-standard data tools, automation techniques and automatic documentation
• Ability to work with system engineers to understand system requirements and to be able to turn conversations and discussions into practical database designs stored in a repository
• In depth working experience of star and snowflake schema designs and from industry experts
• Ability to map data into standard data formats as input into the Informatica ETL developers as requirements
• In depth working experience of relational database, e.g. Oracle, DB2, Teradata, MySQL, MariaDB and Postgres
• Determined best patterns to store and access data in line with usage of the system and transactional needs
• In depth working experience of with ETL (e.g. Informatica, IBM's Infosphere) and SQL queries and stored procedures
• Collaborated with developers, business analysts and architects to establish necessary data model to support the requirements
• Demonstrable experience in developing, publishing, and maintaining all documentation for data models
• Responsible for mapping data flows from source to target systems
• Jointly developed and collaborated with business analysts, data architects, software developers, and DBAs to achieve project objectives
• Experienced with managing meta data for data models

PROFESSIONAL EXPERIENCE DETAILS

Confidential, San Diego, CA

Senior Data Architect

Responsibilities:

• Identifed areas where data can be used to improve organizational activities; proposing and implementing innovative data solutions to support stakeholders in reaching informed Navy investment decisions.
• Supported Senior Confidential Staff in implementing viable surface force automated decision support systems.
• Designed, engineered and maintained data models, translating and visualizing data to meet operational needs; supported feature engineering development and data cross validation.
• Supported development of a tool that supports management and collection of ship focused operator and maintainer performance data and support effectiveness assessments.
• Participated in the testing process through test review and analysis, test witnessing and .
• Provided information assurance Subject Matter Expertise and recommended system enhancements to improve Information Security deficiencies.
• Effectively translated and communicated technical details to senior leadership.
• Assisted in the integration of new technology, design concepts, and systems to improve sharing, collection, and analysis of data with program requirements.
• Supported development and execution of overall program objectives. Established and monitored standards for the quality of programs and documents. Assisted in the resolution of project and program priorities. Assured quality control throughout all contract activities.

Confidential, Seattle, WA

Data Modeler

Responsibilities:

• Working at Starbucks, generated design of data flow framework and design architecture using ability to apply modelling standards to logical ERDs and process models using BPMN.
• Designed and reviewed of data mapping (ETL data mapping with defined technical and business rules).
• Directed application of data modelling concepts (conceptual/ logical/ physical/ semantic, multi-dimensional models (star, snowflake), normalized/denormalized models).
• Applied in-depth understanding data via profiling techniques and analysis (metadata (formats, definitions, valid values, boundaries), relationship/usage).
• Produced quality deliverables in areas of business requirements documentation, logical data modelling, physical modelling, meta-data implementation and data governance.
• Applied experience and knowledge of moderate SQL scripts (creating, reading, running, customizing).
• Demonstrated Hands-on and expert facility with Confidential /Studio Data Architect and Business Architect.
• Interacted with technical leads and work flexibly with them.
• Applied multiple years of experience in requirements and architectural decisions.
• Managed effective relationships with business stakeholders and customers.
• Applied experience with designing architectures and implementing related solutions.
• Created ETL workflows drawing data from disparate sources to populate a decision support platform in support of analytics using Alteryx

Confidential, San Diego, CA

Data Modeler

Responsibilities:

• Created data models and schemas at all levels including conceptual, logical, and physical for both relational and dimensional solutions.
• Integrated disparate data models into coherent enterprise data models.
• Forwarded engineer physical models to create DDL scripts to implement new databases or database changes. Reverse engineer databases and synchronize data models with actual data implementations.
• Created data dictionaries and business glossaries to document data lineages, data definitions and metadata for all business-critical data domains.
• Identified and reconciled inconsistencies in data definitions, e.g., synonyms and homonyms.
• Worked to identify master data (entities and attributes) and capture how data is interpreted by users in various parts of the organization.
• Captured business rules that govern how data is transformed, integrated, and used.

Confidential, San Diego, CA

Data Modeler

Responsibilities:

• Operated as the lead data modeler, championed innovative and streamlined techniques for creating dimensional data models in support of the program.
• Innovated within a team of professional and senior modelers, helped to establish data standards and contribute to the creation of data management best practices for creating high quality data models.

Confidential, Dayton, OH

Data Engineer

Responsibilities:

• Performed data forensics on multiple silo-ed source systems for Air Force contracts management until replacement system is in production.
• Evaluated goodness of fit for Tableau as a departmental BI solution providing managerial insight to upper-level executives.
• Modernized as ETL analyst advising the implementation of induction of various legacy source systems into new replacement system.

Confidential, Dayton, OH

Metadata Analyst

Responsibilities:

• Performed data mining and process analysis to identify opportunities for automation, product creation, quality improvements or reducing time to delivery for a variety of Air Force application initiatives requiring data management or data integration services.
• Designed, planned, and developed programs to optimally extract, transform and load data between data sources and targets as a demonstration of proof of concept or as service to an individual "tenant/customer" needing expert assistance for their initiative.
• Collaborated with the Data Architects, DBAs and Business Intelligence team to design, implement, and support end-to-end data solutions across multiple platforms, environments, domains, and locations in the Air Force data eco system.
• Developed data standards, policies and procedures, as well as establish and maintain standards for data quality conforming to a variety of DOD and Air Force regulations and standards.
• Ensured that data is clean, consistent, and synchronized across platforms consistent with the design and implementation of data cleansing procedures in support of the identification of authorized data sources and logical and physical business rules across the DOD and Air Force.
• Acted as a data integration architect across various business units of the Air Force to identify opportunities for process improvements and data integration re-use of design patterns.
• Worked closely with stakeholders and their teams to understand their data management needs and translating them into requirements for developers.
• Developed data quality metrics for identifying data related issues. Designed prototypes to illustrate and refine requirements.
• Effectively communicated research findings, project progress and success to stakeholders in effective ways using a variety of channels: presentations, webinars, white papers, recommendations for courses action.

Confidential, Dayton, OH

Senior Data Analyst

Responsibilities:

• Responsible for developing architectural blueprints/service patterns, assessing projects for the applicability of enterprise services, applying enterprise thinking to drive value beyond the current project and for delivering high quality estimates, design artifacts and project deliveries
• Articulated the Integration Architecture principles to ensure application/enterprise consistency and rationalization and leverage the integration opportunities among various line of business
• Adhered to enterprise architecture strategies, principals, standards, policies and procedures
• Provided technical leadership in developing vision, strategy, architecture and overall design for assigned integration domains and guidance on API strategy
• Collaborated with Project Managers and technical directors to formulate estimates, develop overall implementation solution plan, and serve as a lead as required
• Reviewed and ensured that architectural designs were consistent, maintainable, flexible, and cost effective
• Provided expertise to identify and translate system requirements into software design documentation
• Provided technical leadership and mentoring throughout the project lifecycle.
• Actively assisted in complex design and technical discussions, reconciling differing opinions and driving decision making process
• Proactively identified reuse and refactoring opportunities
• Articulated the tradeoffs, benefits and risks of all architecture and design solutions
• Provided support for estimation of infrastructure needs for API and integrations solutions
• Lead and guided junior staff in architectural initiatives

Confidential, Cincinnati, OH

Solutions Architect

Responsibilities:

• Working at Kroger in the Point of Sales organization as a key technical resource responsible for oversight of enterprise application governing management, administration and reporting on all Kroger self-checkout lanes. Also lead programmer on conversion program for rollout of replacement software using 4690 programming and Python programming constructs.
• Subject matter expert on predictive analytics tool for configuring and performing optimization of all Kroger checkout lanes across the enterprise using Elastic Search.

Confidential, Dayton, OH

Data Engineer

Responsibilities:

• Operating in a role responsible for development of schema, standards, reverse-engineering processes and generation of repository population and automation for descriptive metadata and metadata production processes for collaborative projects concerning the Air Force's logistic community.
• Key contributor and team member on project dedicated to creating standards and best practices for data governance and data management platform.
• Implemented data governance processes to ensure data integrity by developing efficient processes and controls.
• Analyzed and provided business requirements for database design, data models and data movement.
• Implemented methodologies and technologies for depicting the flow of data within systems and the business requirements, processes and rules visually drawn for analysts and business users.
• Partnered with business users and IT to document business requirements and translated those requirements into actionable data modeling, data movement and translation programs.
• Played a major role in data governance activities working under minimal supervision to deliver software deliverables.
• Created and maintained relevant structures and automated processes centered around building metadata support related to the following areas:
• Data Acquisition
• Data Architecture
• Data Lineage
• Data Quality
• ETL Hardening
• Metadata Standards
• Involved in deployment, testing and administration of IBM's Infosphere Information Server product suite for use as a metadata repository for data relative to the Air Force's GCSS Data Services project.

Confidential, Dayton, OH

Data Architect

Responsibilities:

• Comprehended and translated business needs into data models supporting long- term solutions based on requirements gathering through technical interchange meetings with customers.
• Designed and documented preliminary design of technical solution, solicited feedback and input and proceeded to design of critical design and document presented for final approval of customer.
• Worked with the Application Development team to implement data strategies, build data flows and develop conceptual data models.
• Created logical and physical data models using best practices to ensure high data quality and reduced redundancy.
• Optimized and updated logical and physical data models to support new and existing projects.
• Maintained conceptual, logical and physical data models along with corresponding metadata.
• Developed best practices for standard naming conventions and coding practices to ensure consistency of data models.
• Recommended opportunities for reuse of data models in new environments.
• Performed reverse engineering of physical data models from databases and SQL scripts.
• Evaluated data models and physical databases for variances and discrepancies.
• Validated business data objects for accuracy and completeness.
• Analyzed data-related system integration challenges and propose appropriate solutions.
• Developed data models according to organizational standards.
• Guided System Analysts, Engineers, Programmers and others on project limitations and capabilities, performance requirements and interfaces.
• Reviewed modifications to existing software to improve efficiency and performance.
• Examined new application design and recommend corrections if required.