| Remote - Sr Data Modeler at Remote, Remote, USA |
| Email: [email protected] |
| From: Bharath, Themesoft Inc. [email protected] Reply to: [email protected] Hello, Please find the below job opening and let me know your interest Role: Sr Data Modeler Location: Remote Job Description: The Data Cloud Data Modeler will be joining a world-class data modelling team with a real passion for well-architected analytical software that delivers unparalleled customer success. You will work on canonical Data Cloud data models for horizontal (e.g. sales, service, marketing) and industry-specific analytic applications, helping to shape the structure of data across a much broader range of subject areas than most data modelers see in their careers. Responsibilities: Success will be measured by the individuals ability to deliver well-architected Data Cloud data models at a steady pace of innovation. Hands-on detailed design, development, testing and publishing of canonical data models for OLAP and AI applications built with Data Cloud, as well as OLTP applications. Evaluate and advise product teams to determine data model requirements. Identify overlapping data model requirements across multiple product teams and influence the combined canonical data model design to consensus and consistency. Assist in identifying and articulating gaps in current Data Cloud features necessary to properly support the many use cases for Data Cloud. Collaborate with Data Cloud architects, product owners and developers to design features that close those gaps. Work to improve the data modelling design skills of the product teams we work with. Assist in creating Data Cloud data model documentation and collateral to enable the Salesforce ecosystem to understand and properly adopt the client data model. Seek continuous improvement in Salesforces processes, methods, and tooling to improve our efficiency and effectiveness. Required Qualifications: 10 years of demonstrated hands-on analytical data modelling and design experience across multiple industries for analytical systems. Good knowledge of data modelling principles and best practices including a good understanding of canonical and semantic data modelling concepts. Significant experience in data warehousing, data lakes, ML pipelines, batch and real-time data transformation (ETL/ELT) and processing Significant experience with several of relational, columnar, graph, vector, NoSQL, streaming databases. Ability to quickly grasp technological and business concepts Strong verbal and written communication skills; experience communicating with engineers, software professionals and product management to succinctly explain technical and functional concepts. Experience with the full software lifecycle delivering enterprise software products or large-company analytical information technology projects. Experience and desire to work within a fast-paced environment with short release cycles and an iterative development methodology. Able to work on multiple projects/products simultaneously and comfortable working with minimal specifications A related technical degree required Preferred Qualifications: Experience with modern data stack and analytical technologies such as Apache Iceberg, Snowflake, MongoDB, Neo4j, Neptune, and similar Experience across a variety of business processes and industries; especially communications, media, energy, utilities, financial services, health, manufacturing, consumer packaged goods, retail, non-profit, education, public sector and sustainability. Strong, hands-on knowledge of SQL (or Salesforce SOQL) including performance tuning . Strong knowledge of Salesforce product and platform features, capabilities, and the best use of them such as Data Cloud and Tableau. Good understanding of enterprise architecture principles Experience with Agile development methodologies. Experience with data modelling tools, processes, BI tools, reporting software and data analysis and data analytics. Keywords: artificial intelligence machine learning business intelligence Remote - Sr Data Modeler [email protected] |
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| Sat Nov 23 02:57:00 UTC 2024 |