4 Snow Sight Jobs

Scope & Responsibilities: Enterprise data architecture for a functional domain or for a product group. Design and governs delivery of the Domain Data Architecture / ensures delivery as per design. Ensures consistency in approach for the data modelling of the different solutions of the domain. Design and ensure delivery of data integration across the solutions of the domain. General Expertise: Critical: Methodology expertise on data architecture and modeling from business requirements and functional specifications to data modeling. Critical: Data warehousing and Business intelligence data products modeling (Inmon/Kimball/Data Vault/Codd modeling patterns). Business/Functional knowledge of the domain. This requires business terminology understanding, knowledge of business processes related to the domain, awareness of key principles and objectives, business trends and evolution. Master data management / data management and stewardship processes awareness. Data persistency technologies knowledge: SQL (Ansi-2003 for structured relational data querying & Ansi-2023 for XML, JSON, Property Graph querying) / Snowflake specificities, database structures for performance optimization. NoSQL Other data persistency technologies awareness. Proficient level of Business English & Technical writing Nice to have: Project delivery expertise through agile approach and methodologies experience/knowledge: Scrum, SAFe 5.0, Product-based-organization. Technical Stack expertise: SAP Power Designer modeling (CDM, LDM, PDM) or Erwin Snowflake General Concepts and specifically DDL & DML, Snow Sight, Data Exchange/Data Sharing concepts AWS S3 & Athena (as a query user) Confluence & Jira (as a contributing user) Nice to have: Bitbucket (as a basic user)

Scope & Responsibilities: Enterprise data architecture for a functional domain or for a product group. Design and governs delivery of the Domain Data Architecture / ensures delivery as per design. Ensures consistency in approach for the data modelling of the different solutions of the domain. Design and ensure delivery of data integration across the solutions of the domain. General Expertise: Critical: Methodology expertise on data architecture and modeling from business requirements and functional specifications to data modeling. Critical: Data warehousing and Business intelligence data products modeling (Inmon/Kimball/Data Vault/Codd modeling patterns). Business/Functional knowledge of the domain. This requires business terminology understanding, knowledge of business processes related to the domain, awareness of key principles and objectives, business trends and evolution. Master data management / data management and stewardship processes awareness. Data persistency technologies knowledge: SQL (Ansi-2003 for structured relational data querying & Ansi-2023 for XML, JSON, Property Graph querying) / Snowflake specificities, database structures for performance optimization. NoSQL Other data persistency technologies awareness. Proficient level of Business English & Technical writing Nice to have: Project delivery expertise through agile approach and methodologies experience/knowledge: Scrum, SAFe 5.0, Product-based-organization. Technical Stack expertise: SAP Power Designer modeling (CDM, LDM, PDM) or Erwin Snowflake General Concepts and specifically DDL & DML, Snow Sight, Data Exchange/Data Sharing concepts AWS S3 & Athena (as a query user) Confluence & Jira (as a contributing user) Nice to have: Bitbucket (as a basic user)

Scope & Responsibilities: Enterprise data architecture for a functional domain or for a product group. Design and governs delivery of the Domain Data Architecture / ensures delivery as per design. Ensures consistency in approach for the data modelling of the different solutions of the domain. Design and ensure delivery of data integration across the solutions of the domain. General Expertise: Critical: Methodology expertise on data architecture and modeling from business requirements and functional specifications to data modeling. Critical: Data warehousing and Business intelligence data products modeling (Inmon/Kimball/Data Vault/Codd modeling patterns). Business/Functional knowledge of the domain. This requires business terminology understanding, knowledge of business processes related to the domain, awareness of key principles and objectives, business trends and evolution. Master data management / data management and stewardship processes awareness. Data persistency technologies knowledge: SQL (Ansi-2003 for structured relational data querying & Ansi-2023 for XML, JSON, Property Graph querying) / Snowflake specificities, database structures for performance optimization. NoSQL Other data persistency technologies awareness. Proficient level of Business English & Technical writing Nice to have: Project delivery expertise through agile approach and methodologies experience/knowledge: Scrum, SAFe 5.0, Product-based-organization. Technical Stack expertise: SAP Power Designer modeling (CDM, LDM, PDM) or Erwin Snowflake General Concepts and specifically DDL & DML, Snow Sight, Data Exchange/Data Sharing concepts AWS S3 & Athena (as a query user) Confluence & Jira (as a contributing user) Nice to have: Bitbucket (as a basic user)

Lead Snowflake Data Engineer: Madallion, Data Ingestion, Duplicate Data, Snow sight, Snow SQL A minimum of 5 years of hands-on Snowflake experience Proven expertise in query and performance optimization Strong background in medallion architecture and star schema design Demonstrated experience building scalable data warehouses (not limited to ingesting data from flat files) SnowPro Core Certification is required; SnowPro Advanced certifications in Data Engineering, Data Analysis, or Architecture are highly desirable Snowflake Data Engineer: Data Ingestion, Duplicate Data, Should have used ADF as their main ELT tool and can demonstrate knowledge on how to transfer data using SnowSQL,materialized views and tasks. DBT is a bonus.of the communication, including attachments.