Data Architect- Modeler

At STERIS, we help our Customers create a healthier and safer world by providing innovative healthcare and life science product and service solutions around the globe.

Position Summary

The Enterprise Data Modeler/Architect is responsible for architecting, designing and developing robust and scalable data models and deploying data structures for STERIS enterprise cloud data warehouse, data lake, data hub and other specialized data stores to support reporting, analytic and data science use cases. Works closely with business stakeholders, data engineers, and analysts to understand data and analytics needs and translate them into efficient and effective data models.

The Enterprise Data Architect \ Data Modeler leverages knowledge of data modeling best practices along with cross industry data expertise and data modeling tool expertise. Demonstrates mastery of skills and knowledge and is a mentor, strategist, thought leader, evangelist, champion, plans and leads data modeling activities.

Duties

• Designs, implements, and documents data architecture and data modeling solutions, which include the use of relational, dimensional, and NoSQL databases. These solutions support enterprise information management, reporting, business intelligence, machine learning, data science, and other business use cases.
• Designs and maintain conceptual, logical and physical data models for the enterprise data warehouse (EDW), data lake and other data stores, adhering to best practices and industry standards.
• Collaborate with business stakeholders to understand data requirements and translate them into clear and concise data models.
• Oversee and govern the expansion of existing data repositories and data architecture, and the standardization and optimization of data designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
• Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.
• Conduct assessment and profiling of potential data sources to understand source data structure and content to inform design of target data models.
• Develop and maintain data dictionaries, data glossary, and contribute to develop data catalog metadata models and content.
• Develops, maintains and communicate standards and guidelines for data models and schema objects (e.g., naming standards). Defines and implements administration and control activities related to data warehouse planning and development.
• Work with data engineers to ensure data models are compatible with data extraction, transformation, and loading (ETL/data pipeline) processes.
• Document data models thoroughly, including entity relationships, data definitions, and transformations.
• Research and apply innovations in technology and best practices related to cloud data warehousing, data lakes and data modeling.
• Identify and recommend opportunities to optimize data models for performance and scalability.
• Leads the selection and development of data modelling and design methodology, best practices, tools, and techniques.
• Support data analysts and other data users in understanding and utilizing the data warehouse and data lake. #LI-KS1

Duties - cont'd

• 6+ years of experience in data modelling, preferably with a focus on enterprise cloud data warehouses. Proven experience in designing and developing dimensional models (i.e., star/snowflake schemas).
• Strong conceptual, logical e physical data modelling skills, data profiling skills, data quality assessment, experience with JAD sessions for requirements gathering, creating data mapping documents, writing functional specifications and queries.
• Extensive Information Technology experience in all phases of development life cycle including System Analysis, Planning, Design, Data Modelling, Dimensional Modelling, Testing, implementation and support of data warehouses, data lakes, BI systems, and reporting applications.
• Good understanding of data engineering and ETL, and strong experience in eliciting and documenting requirements for data transformation, data cleansing, data mapping from source to target database schemas or other data sources.
• Experience with data warehouse, data lake and big data cloud data platforms such as Snowflake, AWS Redshift, or Google BigQuery.
• Demonstrable experience in developing, publishing, and maintaining all documentation and metadata for data models. Experience with data catalog tools desired.
• Expert in relational and dimensional structures for large (multi-terabyte) operational, analytical, warehouse and BI systems
• Excellent communication, presentation and collaboration skills.
• Experience designing and implementing role