Assistant Manager - Data Modeler

Assistant Manager

Role: Data Modeler 

Key Responsibilities

Enterprise Data Modelling & Architecture (Primary Focus)

• Support the Lead Enterprise Data Architect in the creation, refinement, and maintenance of enterprise‑level data models.
• Support the data models governance process, ensuring standards, naming conventions, and modelling quality.
• Support and maintain the ER/Idera modelling repository, including version control and model lineage.
• Support projects from a data architecture perspective, ensuring alignment with enterprise modelling practices.
• Build the necessary material and define repeatable processes to run the Data Architecture Assurance Service.
• Contribute to data dictionaries, business glossaries, and enterprise metadata assets.
• Contribute to the creation of data flows, end‑to‑end lineage, and cross‑domain data relationships.
• Support data definitions working groups and other data governance bodies, ensuring consistency and traceability.

Data Platform & Engineering Support

• Ensuring alignment with data architecture standards.
• Support definition of data schemas, ingestion patterns, and ETL/ELT solutions for consumption, validation, storage, and quality control.
• Shape and embed data management best practices across engineering teams (lineage, quality, storage design, master/reference data).
• Support the design and implementation of metadata capabilities, including lineage, business glossary, technical metadata, and stewardship workflows.
• Contribute to data harvesting efforts and support the implementation of business catalogue tools.

Key Technical Skills & Experience

• Strong data modelling skills across conceptual, logical, and physical layers.
• Hands‑on experience with the Microsoft data technology stack (e.g., Azure SQL, Synapse, ADF, Databricks).
• Experience in data collection, integration, and management across distributed systems.
• Understanding of defining data schemas and ETL/ELT solutions for consumption, validation, and secure storage of data.
• Proven experience in designing and implementing metadata management capabilities (lineage, glossary, metadata store, cataloguing tools).
• Experience with data definitions creation and stewardship activities.
• Strong business mindset to interpret organizational business capabilities and translate them into data domains and entities.
• Experience in data harvesting, business catalogue, and data discovery tools.
• Deep understanding of data management concepts including: 
  • Traceability
  • Lineage
  • System of Record (SoR) and System of Authority (SoA)
  • Master Data and Reference Data
  • Metadata lifecycle and curation

Role: Data Modeler 

Key Responsibilities

Enterprise Data Modelling & Architecture (Primary Focus)

• Support the Lead Enterprise Data Architect in the creation, refinement, and maintenance of enterprise‑level data models.
• Support the data models governance process, ensuring standards, naming conventions, and modelling quality.
• Support and maintain the ER/Idera modelling repository, including version control and model lineage.
• Support projects from a data architecture perspective, ensuring alignment with enterprise modelling practices.
• Build the necessary material and define repeatable processes to run the Data Architecture Assurance Service.
• Contribute to data dictionaries, business glossaries, and enterprise metadata assets.
• Contribute to the creation of data flows, end‑to‑end lineage, and cross‑domain data relationships.
• Support data definitions working groups and other data governance bodies, ensuring consistency and traceability.

Data Platform & Engineering Support

• Ensuring alignment with data architecture standards.
• Support definition of data schemas, ingestion patterns, and ETL/ELT solutions for consumption, validation, storage, and quality control.
• Shape and embed data management best practices across engineering teams (lineage, quality, storage design, master/reference data).
• Support the design and implementation of metadata capabilities, including lineage, business glossary, technical metadata, and stewardship workflows.
• Contribute to data harvesting efforts and support the implementation of business catalogue tools.

Key Technical Skills & Experience

• Strong data modelling skills across conceptual, logical, and physical layers.
• Hands‑on experience with the Microsoft data technology stack (e.g., Azure SQL, Synapse, ADF, Databricks).
• Experience in data collection, integration, and management across distributed systems.
• Understanding of defining data schemas and ETL/ELT solutions for consumption, validation, and secure storage of data.
• Proven experience in designing and implementing metadata management capabilities (lineage, glossary, metadata store, cataloguing tools).
• Experience with data definitions creation and stewardship activities.
• Strong business mindset to interpret organizational business capabilities and translate them into data domains and entities.
• Experience in data harvesting, business catalogue, and data discovery tools.
• Deep understanding of data management concepts including: 
  • Traceability
  • Lineage
  • System of Record (SoR) and System of Authority (SoA)
  • Master Data and Reference Data
  • Metadata lifecycle and curation

Role: Data Modeler 

Key Responsibilities

Enterprise Data Modelling & Architecture (Primary Focus)

• Support the Lead Enterprise Data Architect in the creation, refinement, and maintenance of enterprise‑level data models.
• Support the data models governance process, ensuring standards, naming conventions, and modelling quality.
• Support and maintain the ER/Idera modelling repository, including version control and model lineage.
• Support projects from a data architecture perspective, ensuring alignment with enterprise modelling practices.
• Build the necessary material and define repeatable processes to run the Data Architecture Assurance Service.
• Contribute to data dictionaries, business glossaries, and enterprise metadata assets.
• Contribute to the creation of data flows, end‑to‑end lineage, and cross‑domain data relationships.
• Support data definitions working groups and other data governance bodies, ensuring consistency and traceability.

Data Platform & Engineering Support

• Ensuring alignment with data architecture standards.
• Support definition of data schemas, ingestion patterns, and ETL/ELT solutions for consumption, validation, storage, and quality control.
• Shape and embed data management best practices across engineering teams (lineage, quality, storage design, master/reference data).
• Support the design and implementation of metadata capabilities, including lineage, business glossary, technical metadata, and stewardship workflows.
• Contribute to data harvesting efforts and support the implementation of business catalogue tools.

Key Technical Skills & Experience

• Strong data modelling skills across conceptual, logical, and physical layers.
• Hands‑on experience with the Microsoft data technology stack (e.g., Azure SQL, Synapse, ADF, Databricks).
• Experience in data collection, integration, and management across distributed systems.
• Understanding of defining data schemas and ETL/ELT solutions for consumption, validation, and secure storage of data.
• Proven experience in designing and implementing metadata management capabilities (lineage, glossary, metadata store, cataloguing tools).
• Experience with data definitions creation and stewardship activities.
• Strong business mindset to interpret organizational business capabilities and translate them into data domains and entities.
• Experience in data harvesting, business catalogue, and data discovery tools.

• Deep understanding of data management concepts including: 

  • Traceability
  • Lineage
  • System of Record (SoR) and System of Authority (SoA)
  • Master Data and Reference Data
  • Metadata lifecycle and curation

  #LI-KS1

  #KGS

Experience Level

Mid Level