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Data Architect
2 months ago
We are seeking a highly skilled Data Modeller to join our Technology team at Mane Consulting. As a Data Modeller, you will play a pivotal role in crafting Conceptual, Logical, and Physical Data Models that meet organizational needs and align with our Enterprise information model.
Key Responsibilities- Develop and Design Data Models: Create project data models that meet organizational needs and are aligned to our Enterprise information model using conceptual, logical, and physical data models.
- Collaborate with Cross-Functional Teams: Partner with platform architects, data scientists, and analytics professionals to establish a data modeling vision that will drive our success.
- Expand Data Modeling Vision: Continuously identify ways to enrich data and expand the vision for modeling.
- Lead Data Modeling Efforts: Lead and manage data modeling efforts for a new Azure data and analytics platform.
- Ensure Data Consistency and Quality: Ensure consistency, understanding, ease of use, and performance of data by applying and enhancing best practices and standards for data modeling.
- Work with Data Governance and Quality Teams: Work with data governance and quality teams to incorporate processes into models.
- Lead Cross-Functional Agile Teams: Lead workstreams with cross-functional agile teams that include data scientists, data engineers, analysts, and product managers.
- Relational, NoSQL, and Data Lake Technologies: Strong knowledge and experience with relational, NoSQL, and data lake technologies, including Azure SQL, Azure Synapse, and Delta Lake.
- Comprehensive Logical and Physical Data Modeling: Comprehensive logical and physical data modeling for analytics and applications.
- Data Engineering Practices: Strong knowledge and experience with data engineering practices.
- Data Analysis and Visualization: Strong knowledge and experience with modes of visual interaction and information consumption, including data discovery, guided analytics, static reporting, and embedded analytics.
- Data Analysis Types: Strong knowledge and experience with types of data analysis, including descriptive, diagnostic, predictive, and prescriptive analysis.
- Hands-On Experience: 3-5 years of hands-on experience with multiple data modeling techniques, including Data vault logical, dimensional, and physical data modeling.
- Data Engineering Experience: 3-5 years of hands-on experience in data engineering roles, moving data from raw to curated to consumption layers.
- Data Domain and Modeling Experience: Data domain and modeling experience in credit, lending, or financial services preferred.
- Experience in Creating Data Platforms: Experience in creating data platforms across multiple technologies, including Microsoft technologies.
- Strong Understanding of Microsoft BI Suite: Strong understanding of Microsoft BI Suite, Power BI, and ETL/ELT technologies and its architecture.
