Job Summary: 

• Take the lead design and development of data warehouse architecture for a multi-tenant environment.
• Develop the design and architecture of data warehouse in MS Azure
• Optimize existing and new data pipelines.
• Analyze data interfaces and transfer them into the overall architecture of the data lakehouse.
• Establish standards, quality, stability and robustness along the entire ETL chain.
• Define bronze/silver/gold transformations and are responsible for building up a data catalog.
• Define Data warehouse Architecture
• Define Data Integration Architect, integrate, and migrate data from multiple sources, including logical, physical, and dimensional models
• Understand business intelligence needs and reporting requirements to ensure system compatibility
• Provide technical recommendations and engage with partners and other stakeholders throughout the requirements gathering and implementation lifecycle.
• Recommend effective solutions to develop high-performance and highly scalable data solutions.
• Provide expertise in data modeling, database design, data governance, or master data management, including the implementation of tools to support these areas.

Skills on Resume: 

• Data Warehouse Design (Hard Skills)
• Azure Data Services (Hard Skills)
• ETL Optimization (Hard Skills)
• Data Lakehouse Integration (Hard Skills)
• Data Quality Standards (Hard Skills)
• BI and Reporting Analysis (Soft Skills)
• Stakeholder Engagement (Soft Skills)
• Data Governance (Hard Skills)

Job Summary: 

• Develop new ETL procedures to support the business needs. 
• Address user concerns concerning data integrity. 
• Support implemented BI Solutions by monitoring and tuning queries and existing ETLs.
• Work with Enterprise and Solutions architects to provide strategy and direction of applications, information, and technology in support of business strategy. 
• Work out transition/migration plans from the current state.
• Create categorizing and classify information with well-defined structures, definitions, and context to facilitate consistent alignment of business processes with business requirements.
• Development of business glossaries with terminology definitions, standards associated with business rules, and data boundaries.
• Define canonical data models, data flows, etc.
• Work with business and Product Management stakeholders to ensure that project specifications are complete and understood by the Technology team and that the product produced meets all functional and non-functional specifications
• Represent Sovos to technical stakeholders within current and prospective customers

Skills on Resume: 

• ETL Development (Hard Skills)
• Data Integrity Management (Hard Skills)
• BI Solutions Support (Hard Skills)
• Strategic IT Alignment (Soft Skills)
• Migration Planning (Hard Skills)
• Information Classification (Hard Skills)
• Business Glossary Development (Hard Skills)
• Canonical Data Modeling (Hard Skills)

Job Summary: 

• Primarily responsible for the architecture, design, implementation and success of the data warehouse environment
• Lead the vendor selection process for the data warehouse solution
• Build and support data models that will be used across the organization
• Monitor the health, reliability and security of the data warehouse environment
• Enable business users to access data while ensuring a secure environment
• Work with data engineers to guide the development of ETL processes that move data between the various business applications and the warehouse
• Work with key stakeholders within the organization to develop requirements and implement solutions, including getting data loaded into the warehouse and developing data models
• Define standards for ETL processes, data structures, and data organization
• Document processes and procedures
• Evolve Global VAT line of business data strategy and vision to support product strategy and growth.
• Get involved and help build/deliver pieces of the entire data stack (from pipelines to analytics)
• Contribute to the establishment of data management strategies, principles, models, and standards.
• Coordinate proposed solutions with stakeholders from Security and Operations to ensure the smooth execution of a comprehensive solution that is secure and well-operated

Skills on Resume: 

• Data Warehouse Architecture (Hard Skills)
• Vendor Selection (Soft Skills)
• Data Modeling (Hard Skills)
• Data Warehouse Monitoring (Hard Skills)
• User Access Management (Soft Skills)
• ETL Process Guidance (Hard Skills)
• Requirement Development (Soft Skills)
• Data Strategy Development (Hard Skills)

Job Summary: 

• Establish a long-term strategic data architecture vision and data standards for enterprise systems.
• Lead the conception, design, development, and deployment of EDW data architecture and related data models and provide ongoing support.
• Design, develop, test, and maintain data warehouse ETL processes, and perform systems integration.
• Design, develop, and manage a set of data models to support Power BI and SSRS reports to maximize runtime efficiency and reduce complexity and redundancy.
• Perform ongoing evaluation of the organization's current data infrastructure to identify gaps and develop plans for integrating data from existing third-party systems.
• Establish processes for governing the identification, collection, and use of corporate metadata, and take steps to assure metadata accuracy and validity.
• Establish methods and procedures for tracking data quality, completeness, redundancy, compliance, and improvement.
• Assess and determine governance, stewardship, and frameworks for managing data across the enterprise.
• Create strategies and plans for data capacity planning, data security, life cycle data management, scalability, backup, disaster recovery, business continuity, and archiving.
• Recognize and identify potential areas where existing policies and procedures require change, or where new ones are needed.
• Formulate and maintain data models and policies and procedures for functional design.
• Provide technical recommendations to senior managers and technical staff in the development and implementation of databases or documentation.
• Research upgrades and new database technologies.
• Collaborate with project managers and business leaders for all projects involving enterprise data.

Skills on Resume: 

• Data Architecture Vision (Hard Skills)
• EDW Data Design (Hard Skills)
• ETL Development (Hard Skills)
• Data Modeling for BI (Hard Skills)
• Data Infrastructure Evaluation (Hard Skills)
• Metadata Governance (Hard Skills)
• Data Quality Management (Hard Skills)
• Data Strategy and Planning (Hard Skills)

Job Summary: 

• Lead in the design of the technical and information architecture for the enterprise data warehouse, including all information structures
• Focuses on enterprise-wide data modeling and database design
• Works with business stakeholders on contextual dimensions, facts, measures
• Creates logical and physical data models, mapping logical to physical
• Designs, develops, tests, monitors, manages and validates data warehouse activity, including data extraction, transformation, movement, loading, cleansing and updating processes
• Coordinates with other Data Warehouse IT stakeholders to ensure the overall health and performance of the data warehouse environment
• Works with end users to translate business questions and requirements into applications that employ the appropriate reporting tools
• Experience with Agile methodology, writing user stories and acceptance criteria, and grooming the backlog
• Assists in monitoring system performance, reliability, availability, and recoverability of the DW environment
• Assists in the evaluation, selection, testing, and optimization of BI/DW-related hardware and software products
• Document the data architecture and environment to maintain a current and accurate view of the larger data picture.
• Serve as an organizational data SME for data analysts, SQL developers, and other end users who access the EDW.
• Collaborate and engage with external IT solution partners to ensure the requirements of any outsourced work are fully understood, accurately and thoroughly developed, and delivered on time.

Skills on Resume: 

• Architecture Design (Hard Skills)
• Data Modeling (Hard Skills)
• Data Mapping (Hard Skills)
• ETL Management (Hard Skills)
• Stakeholder Collaboration (Soft Skills)
• Agile Experience (Soft Skills)
• Performance Monitoring (Hard Skills)
• Data Documentation (Hard Skills)

Job Summary: 

• Devise and utilize algorithms and models to mine big data stores
• Perform data and error analysis to clean, normalize and validate data for uniformity and accuracy.
• Analyze EMR data by defining data requirements, preparing data for processing by organizing information, checking for invalid and missing data, and adjusting and weighing the raw data.
• Process large amounts of data using statistical software and relational database software.
• Identify relationships and trends in data, as well as factors that may influence decision-making.
• Design, produce, analyze, and debug routine data reports for internal and external customers.
• Report results of statistical analyses in the form of graphs, charts, tables, and written reports using statistical, spreadsheet and/or word processing software.
• Provide technical support to customers including answering questions, troubleshooting problems and assisting in modification of program code.
• Develop documentation for all analyses to include storage documentation of all files (program code, data sets, output), thoroughly documenting program code and archiving data sets when not in use.
• Check program code for adherence to specifications and check output for correct results.
• Develop quantitative measures to assess program effectiveness (e.g., internal quality control measures.)
• Maintains completeness of the data warehouse by ensuring uninterrupted access to data from disparate data sources, including establishing access to new sources of data.

Skills on Resume: 

• Algorithm Development (Hard Skills)
• Data Cleaning (Hard Skills)
• EMR Data Analysis (Hard Skills)
• Statistical Software Proficiency (Hard Skills)
• Trend Identification (Hard Skills)
• Data Reporting (Hard Skills)
• Technical Support (Soft Skills)
• Documentation Development (Hard Skills)