Closely work with the BI and data engineers and business teams to ensure the effective translation of business and technical requirements into the logical, physical and conceptual data models for your Data Warehouse to enable self service BI.

More Uses of the Data Warehouse Toolkit:

  • Manage work with the Data Technology teams (PMO, Business analysis, Data Architecture, Information Governance, Operational Data, Data Acquisition, Analytics and Infrastructure) to support and innovate on the Enterprise Data Warehouse platform.
  • Be accountable for creating and maintaining appropriate Data Analytics solution (in collaboration with ETL, data architecture, and business requirements) to support Enterprise Data Warehouse and BI capabilities.
  • Ensure you administer; lead the acquisition and development of effective master data management and Data Warehouse solutions that deliver high quality, complete, and consistent data as the foundation for enabling the goals of your business strategy.
  • Support the command overhead and service cost center budget preparation, execution tracking, and reporting through data extraction via the financial system of record and Data Warehouse.
  • Maintain a scalable structure for business information, understand current and emerging technologies, and align applications with business priorities and growth.
  • Standardize: partner with other functions in AWS as Data Warehouse/business intelligence, business development, finance, marketing, recruiting, and compensation.
  • Devise: database products, system migrations, project management, customer and partner communications, partner enablement and cloud adoption projects.
  • Warrant that your business supports other business executives and departmental leaders in making strategic, data driven decisions, in regard to new products, additional use cases, customer segments, investments, among other subjects.
  • Supervise the integration and staging of data, and the development and maintenance of the data lakes, Data Warehouse and data marts, for use by analysts throughout your organization.
  • Standardize: prototype solutions, prepare test scripts, and conduct tests for data replication, extraction, loading, cleansing, and data modeling for Data Warehouses.
  • Drive and oversees initiatives to meet and even exceed performance expectations, key metrics, and enable overall profitability of the business.
  • Use tactical tools, which can search Data Warehouses at a trade level, filter unwanted information and display the remaining results concisely, for subsequent analysis.
  • Confirm your organization develops and maintains complex data storage structures needed to support Data Warehouse functions to ensure data is maintained in consistent formats.
  • Recognize and drive opportunities to lead technical considerations in designing Data lakes, Data Warehouses, IT operations analytics based on Machine learning methodologies, and similar large scale Data products.
  • Introduce and advocate for industry best practices of a modern Data Warehouse as customer centric, adaptable, automated, elastic, governed, secure, etc.
  • Manage to clearly communicate instructions and sensitive information down the line for data analytics and data warehousing personnel to effectively execute duties.
  • Standardize: partner with security and privacy teams to ensure data is secure and in compliance with GDPR, CCPA, data privacy, and data retention policies.
  • Create summary statistics/reports from Data Warehouses, marts, and operational data stores to establish testing criteria and create model training and validation data sets.
  • Be accountable for architecting and implementing ETL and data replication solutions that provide timely and accurate ingestion of data to Data Warehouses and data lakes.
  • Ensure your operation complies; mentors and provides ongoing guidance to Business Analysts, Super Users and Technical Application Support Analysts on complex issues and errors.
  • Warrant that your group leads the data analytics and data warehousing efforts in research, development, and implementation of appropriate data systems that lead to improved business performance and achievement of overall business goals.
  • Identify: act as an expert technical resource for cloud data modelling, Data Warehouse architecture and analysis efforts to support business team goals.
  • Warrant that your organization gathers stakeholder requirements and use cases for new data sources to be added to the Data Warehouse, prioritizing tasks to meet project deadlines.
  • Coordinate with the database administration group to ensure day to day activities (statistics collection and reporting) are performing in the most efficient manner (Data Warehouse and big data environments).
  • Govern: design and develop framework for increasing the overall efficiency of bringing data into the data lake, processing and delivery of data; encode best practices into reusable tools that can be shared across the team.
  • Be an Azure platform evangelist for advanced analytics scenarios like modernizing your legacy Data Warehouse and migrating to the cloud, new modern data warehousing deployments and end to end analytics solutions.
  • Develop and maintain data structures which draw information from multiple sources of data as corporate databases, corporate Data Warehouses and other.
  • Become a consumer lending data expertise, utilizing the Data Warehouse to inform modeling approaches, understand customer behavior, research outliers, and prepare data for usage by the quantitative modeling team.
  • Ensure you convey; recommend and design system or tool changes or enhancements, giving primary consideration to the feasibility, maintainability, internal customer needs, and overall cost/benefit and quality requirements.
  • Develop: implement and administer cloud platform and on premise databases and Data Warehouse solutions using automation, scripting and infrastructure as code.

 

Categories: Articles