Description
Azure Data Modeler
Environment
Are you an enthusiastic Azure Data Modeler who is passionate about all things data integration, ETL, Data Warehousing, Data Factory? In this long-term role, you will join a DevOps team working on different challenges like setting-up the data platform which will service multiple Biz Dev/Ops teams of the company (Risk, Finance etc) on a common platform native cloud (Azure).
Your role as an Azure Data Modeler:
- Be responsible for the development of the conceptual, logical, and physical data models, the modelling of the RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
- Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
- Define and govern data modelling and design standards, tools, best practices, and related development for enterprise data models.
- Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
- Develop and maintain ETL specifications for data integration development
- Define and deliver consistent data modelling and data architecture standards, methodologies, guidelines and techniques
- Serve as source of knowledge of data warehouse data architecture practices and processes
- Participate in the development of enterprise standards and guidelines for data model quality and accuracy to support information management
- Audit project level data model quality deliverables to ensure that practices and standards are met
- Create and maintain data dictionary documents, table and data lineage models and produce artifacts to support project development
Your Skills as an Azure Data Modeler:
- 5+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
- Solid experience with Datamodelling, data warehouse design and data lake concepts and practices
- Experience with data warehouse and enterprise big data platforms in multi-data-center contexts required
- Knowledge and experience with Data Vault methodology
- Good knowledge of metadata management, data modelling, and related tools
- Exposure working in a Microsoft Azure Data Platform environment;
- Exposure working with Azure Data Factory, Azure Storage (Blob or Data Lake), Databricks, SQL Azure DB, SQL Azure DW and Azure DevOps - CI/CD
- Experience in communication and presentation
- Experience in Agile (Scrum) way of working