

Dabster
Data Modeller
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Modeller with a 6-month contract, offering a pay rate of "X" per hour. Required skills include expert knowledge of FSLDM, extensive Teradata experience, and proficiency in Informatica. Banking/Financial Services domain expertise is essential.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
March 3, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United Kingdom
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Logical Data Model #Data Science #Data Processing #Data Warehouse #Metadata #Business Analysis #Data Modeling #Teradata SQL #Data Lineage #BTEQ #Data Governance #IICS (Informatica Intelligent Cloud Services) #Informatica PowerCenter #Compliance #Informatica #Scala #Teradata #Data Pipeline #FastLoad #Data Lake #Cloud #Data Lakehouse #MLOAD (MultiLoad) #Data Management #SQL (Structured Query Language)
Role description
Key Responsibilities
• Data Modeling: Lead the implementation and customization of the Teradata FSLDM (Financial Services Logical Data Model) to ensure it meets the specific needs of the Lakehouse program.
• Architecture Design: Design and maintain the Data Lakehouse layers (Bronze/Silver/Gold or Raw/Integrated/Access) to support massive scales of financial data.
• ETL/ELT Development: Architect and develop robust data pipelines using Informatica (PowerCenter or IICS) to migrate data from disparate sources into Teradata and the Lakehouse environment.
• Performance Tuning: Optimize Teradata SQL and Informatica mappings for high-volume data processing and complex financial calculations.
• Data Governance: Ensure compliance with financial regulations by implementing data lineage, quality checks, and metadata management within the FSLDM framework.
• Stakeholder Collaboration: Work closely with Business Analysts and Data Scientists to translate financial business requirements into scalable technical schemas.
Technical Requirements
• Core Model: Expert-level knowledge of FSLDM (Financial Services Logical Data Model) is mandatory.
• Primary Database: Extensive experience with Teradata (Vantage, Architecture, Utilities like BTEQ, FastLoad, MultiLoad).
• Integration Tools: Advanced proficiency in Informatica (PowerCenter/Informatica Intelligent Cloud Services).
• Lakehouse Experience: Proven experience in building or maintaining Data Lakehouse architectures (combining the flexibility of data lakes with the performance of data warehouses).
• Domain Knowledge: Strong understanding of Banking/Financial Services domains (Risk, Finance, Regulatory Reporting, or Retail Banking).
Key Responsibilities
• Data Modeling: Lead the implementation and customization of the Teradata FSLDM (Financial Services Logical Data Model) to ensure it meets the specific needs of the Lakehouse program.
• Architecture Design: Design and maintain the Data Lakehouse layers (Bronze/Silver/Gold or Raw/Integrated/Access) to support massive scales of financial data.
• ETL/ELT Development: Architect and develop robust data pipelines using Informatica (PowerCenter or IICS) to migrate data from disparate sources into Teradata and the Lakehouse environment.
• Performance Tuning: Optimize Teradata SQL and Informatica mappings for high-volume data processing and complex financial calculations.
• Data Governance: Ensure compliance with financial regulations by implementing data lineage, quality checks, and metadata management within the FSLDM framework.
• Stakeholder Collaboration: Work closely with Business Analysts and Data Scientists to translate financial business requirements into scalable technical schemas.
Technical Requirements
• Core Model: Expert-level knowledge of FSLDM (Financial Services Logical Data Model) is mandatory.
• Primary Database: Extensive experience with Teradata (Vantage, Architecture, Utilities like BTEQ, FastLoad, MultiLoad).
• Integration Tools: Advanced proficiency in Informatica (PowerCenter/Informatica Intelligent Cloud Services).
• Lakehouse Experience: Proven experience in building or maintaining Data Lakehouse architectures (combining the flexibility of data lakes with the performance of data warehouses).
• Domain Knowledge: Strong understanding of Banking/Financial Services domains (Risk, Finance, Regulatory Reporting, or Retail Banking).





