CDW Digital Velocity GroupManaging Consultant (Data Architect)(Azure, AWS, GPC, Cloudera, Most RDBMS, Snowflake, Python, Airflow, Terraform, Ansible, Alation, Purview, Erwin)Big Data, Cloud Architect, and Project Delivery Leadership with 25 years’ experience designing and delivering BI Analytics and Big Data projects for Fortune 100 companies. Noel has extensive experience designing for both Transactional and Dimensional data models as well as unstructured data models. As a Data Architect, Noel has been involved in the design of Data Migration and ETL Projects with very large budgets, from architecting and data management to project management of large-scale data integration and migration projects. Noel has been heavily involved in managing multiple vendors and global project teams as well as developing architectural frameworks that align strategy, processes, and IT assets with business goals. Below is an example of these:Assist Clients in Healthcare, Energy, and Distribution providing roadmaps for implementation of Cloud environments. Additionally, work in assisting stand up of these technologies for Azure and AWS as well as in the migration of on premises assets to the cloud.

Innowatts is a company providing a PaaS to the Electrical power providers located throughout the United States, Southern America, and Europe. Data is provided to the PaaS by either delivery through a sftp server or through customer provided API’s. Once data is received it is reviewed by data analyst and mapped to the IWCDM (Innowatts Common Data Model). The data is then loaded to the input AWS bucket where the Pyspark ingestion process consumes the data performing various transformations as needed and loaded to the IWCDM. At the conclusion of the successful ingestion, the post ingest process then consumes the data from the IWCDM and applies the data to the desire model that the customer desires; usually related to utilization of KWs by residence or business users over a variety of time. The output is loaded to Redshift Tables where it is displayed in a customer portal dashboard. The customer has a variety of options of applying different data sets against a model and additionally selecting a variety of features to apply against the model (mathematical model) to receive additional output.The Innowatts PaaS is totally an AWS platform. The client’s data received is loaded initially by Informatica by once placed in the input AWS bucket future processing is performed by PySpark programs through Visualization in Tableau.

Support the BI and Analytics Group providing Architectural review and input in Business Intelligence, Data Warehousing, and Advanced Analytics. Providing additional data engineering services in the form of creating data pipelines for streaming data using Spark Streaming and Kafka.Worked with Analytics team providing data to Azure Data Lake II through the creation of data pipelines using Azure Data Factory. Worked with various groups with the IT organization at Noble to provide modeling, architectural, and other technology selections. Developing a variety of Pipelines in Python and Spark for data movement and streaming.Created the Data Catalogue for all data assets with the Organization to provide a centralized location that both business users as well as technical users can enhance the Corporate Knowledge of data assets by editing and inputting additional information regarding an artifact that will be captured with the application for sharing by the entire Organization.

Engaged in the migration of Netezza Warehouse to AWS Redshift in a private cloud environment. Working with various migration team members to design the process for the migration of data structures, and code processes to the RedShift environment. Tools used was PySpark and Lambda to increase the speed of loads dramatically. The phase 1 and phase 2 of this migration is completed and the enterprise is processing from the RedShift Clusters in AWS.Additional work includes Architecting the design and coding the implementation data ingestion process for a Recommendation Engine that processed terabytes of transactional data. Additional project activities included the development of a data lake to be used primarily for the automation of Analytical discovery within various business units. The data lake is a schema on read design using a virtual schema enabled with Hadoop, Glue metadata store, Athena and Spectrum using Pyspark. This architecture includes the use of the data files stored in S3 in parquet file format, then using Glue and Athena (or imply) for enabling virtual schema on read. If the user’s desired data is located through the Athena query interface; using SQL; then the data set can be loaded to an EMR cluster for development of a model. All work is saved in GitHub and available for use by being boot strap to load on startup of their EMR cluster to continue working with this same data and model. Using this process, the EMR Cluster can be terminated when the Data Scientist is not working with it so unnecessary charges are not incurred.

Engaged as a Senior Enterprise Architect and Project Delivery Leader with 25 years' experience designing and delivering business analytics and data warehousing projects for Fortune 1000 companies. Extensive experience designing data models, managing multiple vendors and global project teams as well as developing architectural frameworks that align strategy, processes and IT assets with business goals.Assigned BP - Worked as a Big Data & Analytics Architect for Innovation Lab at British Petroleum (BP) located in Houston, Texas. The purpose of the Innovation Lab is to provide PoC that provide business users with the knowledge that an application of Technology can provide proven business value. Assigned Shell Corporation - Engaged as Project Manager for downstream supply project at Shell Corporation, Houston, TX. Based on prior work within SOPUS; as well as in other clusters around the globe (e.g. Faro); indications are that substantial value may available by more effectively managing the interface between S&D, RMO, STUSCO, Refining, B2B and Fuels on the West Coast (Seahawk) and Mid-Continent (Firebird). This would involve potential shifting of current interface points with STUSCO further back towards the refinery to a point which would allow Supply to report cleaner P&L results (minimizing exposures), while allowing STUSCO to manage the Products inventory more effectively with various hedging instruments. Additionally, there is a potential for a change in scope of activities for STUSCO where more value could be captured with further integration of decision making and hedging of Product make and disposal.Assigned CSRA - The Office of Health and Human Resources engaged CSRA to produce the ability to consume large volumes of medical claims records from Trusted Partners (BCBS, MediGold, Humana, etc.) for the purposes of applying a variety of SAAS designed Analytical Models against the ingested data to aid in identifying fraudulent claims activity.

As Sr. Solution Architect, there is a dual role of working with Account Executives to provide solutions to potential clients as well as working with CS to assist in delivering these solutions to the clients. Task would include detail involvement in scoping, project management, and delivery.Projects to date have included both traditional data warehousing as well as Active DW, Operational BI, Application Integration, and Analytical System development. My primarily worked in Downstream O&G with several Majors in the Houston, TX area. I was also the Solution Architect for Business Intelligence engagements / projects with Symantec and Apple Computer in San Jose, CA area.

As Enterprise Architect led design and implementation the Enterprise Data Management Architect from conceptual design to actual implementation of various status of the Architectural concepts which included: * Operational Data Store* Master Data Management for Customer and Product* Enterprise Data Warehouse* BI Data Marts* Data Integration for Supply Chain (Manhattan)As Enterprise Architect, I was responsible for the creation and documentation of the Enterprise Data Management Framework as well as for other Enterprise level documentation including Data Governance. Assisted in providing Road Map to ensure IT was aligned with business needs.As Data Services Mgr, I was charged with the creation of management of data movement between applications. With a team that varied between 10-15 on shore and 4 to 8 offshore ETL Developers more than 1400 sequences consisting of approximately 4,500 individual DataStage Jobs were created. These jobs move data between all enterprise systems including Marketing, Finance, eCom, and Manhattan Supply chain for all Divisions of the Men's Wearhouse.Of the various systems that were integrated, the Manhattan Supply Chain products were especially challenging. Of the numerous available modules, the following were implemented: WMOS, EEM, Dom, REPL, RLM, and Planning. Additionally, MID Allocation was included in this integration of products. As the current release of Manhattan consisted of individual products, each with its own under lying database and unique schema, the challenge was to integrate in real time or near real time across these platforms from TMW's Point Of Sales system. A variety of IBM DataStage products were utilized to accomplish this task including IDS for creation of Web Services that were used mainly in the integration with the WebSphere ecommerce products.