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Form of workJob Description
Role: Data Modeler with Collibra Domain
Location : 100% remote
Total position : 5
Duration: 1 year +
Collibra Domain Data Modeler - Securities
Responsibilities:
Work on the development of conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices.
Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
Knowledge of data modelling and Metadata technologies and methods of storing reference data and definitions
Experience in linking conceptual, logical, and physical models to provide a tangible value to the business
Maintain strict governance and standards on the usage of transaction data and models
Work with business stakeholders 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.
Hands-on modelling, design, configuration, installation, performance tuning, and sandbox POC.
Requirements:
Experience in Collibra data modelling and metadata tools
Expertise in data modelling principles/methods including conceptual, logical & physical Data Models
5+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
Knowledge of more than one financial asset class - systems, tools, processes
Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-centre contexts required.
Good knowledge of metadata management, data modelling, and related tools (Erwin or ER Studio or others) required.
Experience in working with combined on-, near- or offshore technology delivery teams
Location : 100% remote
Total position : 5
Duration: 1 year +
Collibra Domain Data Modeler - Securities
Responsibilities:
Work on the development of conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices.
Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
Knowledge of data modelling and Metadata technologies and methods of storing reference data and definitions
Experience in linking conceptual, logical, and physical models to provide a tangible value to the business
Maintain strict governance and standards on the usage of transaction data and models
Work with business stakeholders 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.
Hands-on modelling, design, configuration, installation, performance tuning, and sandbox POC.
Requirements:
Experience in Collibra data modelling and metadata tools
Expertise in data modelling principles/methods including conceptual, logical & physical Data Models
5+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
Knowledge of more than one financial asset class - systems, tools, processes
Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-centre contexts required.
Good knowledge of metadata management, data modelling, and related tools (Erwin or ER Studio or others) required.
Experience in working with combined on-, near- or offshore technology delivery teams
