Planning, migration, and integration of multiple on-prem data sources into a modern Azure data architecture. The focus of this initiative will be data migration and integration 10+ datasets including new and historical data, time-series and trending data and some additional datasets into a data lake. As the lead Data Modeler, you will need to develop conceptual data models, detailed logical data models for client’s data objects, and collaborate with database developers and data engineers to implement the data models in the cloud data lake. Effective communication, and technical programming skillsets will be important to be a successful candidate
Key Responsibilities
Requirements Analysis: Work closely with stakeholders, such as business analysts and end-users, to understand the data requirements of a system or project.
Conceptual Modeling: Create a high-level, abstract representation of the data requirements, known as a conceptual data model. This model defines entities, their attributes, and the relationships between them.
Logical Modeling: Develop a detailed logical data model based on the conceptual model. This involves defining tables, columns, primary keys, foreign keys, and other database-specific details.
Normalization: Ensure that the data model is normalized, which means organizing data in a way that minimizes redundancy and dependency issues.
Data Integrity: Enforce data integrity constraints to maintain the accuracy and consistency of the data within the database.
Collaboration with Database Developers: Work closely with database developers and administrators to implement the data model in the cloud.
Documentation: Create and maintain documentation for the data model, including diagrams, data dictionaries, and any other relevant information.
Programming/Development: Utilizing your expertise in SQL/T-SQL, Python, C#, No-SQL, ADF, Event Hub, Databricks, Unity Catalog, Delta Lake, CosmoDB, Git, Azure DevOps, and modern architecture design principles.
Required Skills
Client facing / Business stakeholder management: Ability to lead client conversations, develop new opportunities and turn them into revenue generating initiatives.
Analytical skills: strong data analysis skills and know how to appropriately evaluate metrics for informed decision making
Communication abilities: communicate with a large number of stakeholders that span across the business and IT through both verbal and written communication
Problem-solving capabilities: creative thinker with excellent problem-solving abilities
Minimum of 7 years of hands-on experience in data modeling.
Proven capacity for managing several parallel initiatives while identifying and balancing priorities effectively.
Strong expertise in SQL/T-SQL, Python, C#, No-SQL, ADF, Event Hub, Databricks, Unity Catalog, eDelta Lake, CosmoDB, Git, and Azure DevOps.
Experience in Historical Data Migration, Bulk Data Migration, Technical Documentation, Creating ERD Diagrams, and Data Engineering via ADF Databricks.
Familiarity with PODS data models and/or ERwin data modeling tools is a bonus.
Azure Data Engineer Associate (Microsoft Certified), Certified Data Management Professional (CDMP) or Certified Data Modeler (CDM), or Azure Data Fundamentals certification preferred.w2