Technical Architect

Job Summary

The requirements for a Senior Data Modeller... The requirements for a Senior Data Modeller role are more detailed:  P1 – Critical / Must‑Have Skills Strong experience in conceptual, logical, and physical data modelling Solid Markets domain knowledge (trades, instruments, lifecycle events, reference data) Proven experience designing data models for data products (not single systems) Ownership of entity definitions, relationships, keys, and constraints Experience with enterprise data modelling tools (IDERA ER/Studio and/or ERwin) Ability to translate business concepts into robust data structures Strong understanding of data governance, lineage, and auditability Ability to collaborate effectively with data engineers and SMEs Clear communication of modelling decisions and trade‑offs P2 – Important / Value‑Adding Skills Experience modelling regulatory or surveillance data (e.g. Market Abuse) Practical experience designing BigQuery‑optimised schemas, including: Denormalisation patterns Partitioning and clustering Cost/performance trade‑offs Experience aligning models to ODP / FDP / CDP layering Familiarity with ISDA Common Domain Model (CDM) Experience working in cloud‑native data platforms (GCP) Ability to define and enforce modelling standards and naming conventions Supporting impact analysis and controlled model evolution P3 – Desirable / Differentiating Skills Deep hands‑on experience applying ISDA CDM in real implementations Experience influencing or shaping enterprise data modelling standards Exposure to data cataloguing, lineage, or governance tooling Experience mentoring or reviewing models created by others Ability to challenge requirements that lead to unnecessary complexity Strong experience balancing operational vs analytical modelling needs Prior work in large‑scale transformation or strategic programmes Skill Matrix Skill or Category Mandatory / Non-Mandatory Evaluation Focus Conceptual, Logical & Physical Data Modelling Mandatory Strong expertise in designing conceptual, logical, and physical data models aligned with business and enterprise requirements. Capital Markets Domain Knowledge Good to have Deep understanding of trades, instruments, lifecycle events, reference data, and market data concepts. Data Product Modelling Mandatory Experience designing enterprise-scale data products rather than system-specific data models. Data Architecture & Model Design Mandatory Ownership of entity definitions, relationships, keys, constraints, and reusable modelling patterns. Enterprise Data Modelling Tools Mandatory Hands-on expertise with ER/Studio, ERwin, or equivalent data modelling platforms. Business to Data Translation Mandatory Ability to convert business concepts and requirements into scalable and robust data structures. Data Governance & Lineage Mandatory Understanding of governance, lineage, auditability, metadata management, and data quality principles. Stakeholder Collaboration & Communication Mandatory Ability to work effectively with SMEs, business stakeholders, architects, and data engineers while clearly articulating modelling decisions. BigQuery Data Modelling Mandatory Experience designing BigQuery-optimized schemas considering scalability, performance, and cost efficiency. GCP Data Platform Experience Mandatory Experience working within GCP-native data ecosystems and modern cloud data architectures. Analytical & Solution Design Thinking Mandatory Ability to evaluate modelling trade-offs and design fit-for-purpose analytical and operational models. , Regulatory / Surveillance Data Modelling Non-Mandatory Experience modelling regulatory reporting, surveillance, or market abuse data domains. BigQuery Performance Optimization Non-Mandatory Knowledge of denormalization, partitioning, clustering, and perfo

Key Responsibilities

The requirements for a Senior Data Modeller... The requirements for a Senior Data Modeller role are more detailed:  P1 – Critical / Must‑Have Skills Strong experience in conceptual, logical, and physical data modelling Solid Markets domain knowledge (trades, instruments, lifecycle events, reference data) Proven experience designing data models for data products (not single systems) Ownership of entity definitions, relationships, keys, and constraints Experience with enterprise data modelling tools (IDERA ER/Studio and/or ERwin) Ability to translate business concepts into robust data structures Strong understanding of data governance, lineage, and auditability Ability to collaborate effectively with data engineers and SMEs Clear communication of modelling decisions and trade‑offs P2 – Important / Value‑Adding Skills Experience modelling regulatory or surveillance data (e.g. Market Abuse) Practical experience designing BigQuery‑optimised schemas, including: Denormalisation patterns Partitioning and clustering Cost/performance trade‑offs Experience aligning models to ODP / FDP / CDP layering Familiarity with ISDA Common Domain Model (CDM) Experience working in cloud‑native data platforms (GCP) Ability to define and enforce modelling standards and naming conventions Supporting impact analysis and controlled model evolution P3 – Desirable / Differentiating Skills Deep hands‑on experience applying ISDA CDM in real implementations Experience influencing or shaping enterprise data modelling standards Exposure to data cataloguing, lineage, or governance tooling Experience mentoring or reviewing models created by others Ability to challenge requirements that lead to unnecessary complexity Strong experience balancing operational vs analytical modelling needs Prior work in large‑scale transformation or strategic programmes Skill Matrix Skill or Category Mandatory / Non-Mandatory Evaluation Focus Conceptual, Logical & Physical Data Modelling Mandatory Strong expertise in designing conceptual, logical, and physical data models aligned with business and enterprise requirements. Capital Markets Domain Knowledge Good to have Deep understanding of trades, instruments, lifecycle events, reference data, and market data concepts. Data Product Modelling Mandatory Experience designing enterprise-scale data products rather than system-specific data models. Data Architecture & Model Design Mandatory Ownership of entity definitions, relationships, keys, constraints, and reusable modelling patterns. Enterprise Data Modelling Tools Mandatory Hands-on expertise with ER/Studio, ERwin, or equivalent data modelling platforms. Business to Data Translation Mandatory Ability to convert business concepts and requirements into scalable and robust data structures. Data Governance & Lineage Mandatory Understanding of governance, lineage, auditability, metadata management, and data quality principles. Stakeholder Collaboration & Communication Mandatory Ability to work effectively with SMEs, business stakeholders, architects, and data engineers while clearly articulating modelling decisions. BigQuery Data Modelling Mandatory Experience designing BigQuery-optimized schemas considering scalability, performance, and cost efficiency. GCP Data Platform Experience Mandatory Experience working within GCP-native data ecosystems and modern cloud data architectures. Analytical & Solution Design Thinking Mandatory Ability to evaluate modelling trade-offs and design fit-for-purpose analytical and operational models. , Regulatory / Surveillance Data Modelling Non-Mandatory Experience modelling regulatory reporting, surveillance, or market abuse data domains. BigQuery Performance Optimization Non-Mandatory Knowledge of denormalization, partitioning, clustering, and perfo

Skill Requirements

The requirements for a Senior Data Modeller... The requirements for a Senior Data Modeller role are more detailed:  P1 – Critical / Must‑Have Skills Strong experience in conceptual, logical, and physical data modelling Solid Markets domain knowledge (trades, instruments, lifecycle events, reference data) Proven experience designing data models for data products (not single systems) Ownership of entity definitions, relationships, keys, and constraints Experience with enterprise data modelling tools (IDERA ER/Studio and/or ERwin) Ability to translate business concepts into robust data structures Strong understanding of data governance, lineage, and auditability Ability to collaborate effectively with data engineers and SMEs Clear communication of modelling decisions and trade‑offs P2 – Important / Value‑Adding Skills Experience modelling regulatory or surveillance data (e.g. Market Abuse) Practical experience designing BigQuery‑optimised schemas, including: Denormalisation patterns Partitioning and clustering Cost/performance trade‑offs Experience aligning models to ODP / FDP / CDP layering Familiarity with ISDA Common Domain Model (CDM) Experience working in cloud‑native data platforms (GCP) Ability to define and enforce modelling standards and naming conventions Supporting impact analysis and controlled model evolution P3 – Desirable / Differentiating Skills Deep hands‑on experience applying ISDA CDM in real implementations Experience influencing or shaping enterprise data modelling standards Exposure to data cataloguing, lineage, or governance tooling Experience mentoring or reviewing models created by others Ability to challenge requirements that lead to unnecessary complexity Strong experience balancing operational vs analytical modelling needs Prior work in large‑scale transformation or strategic programmes Skill Matrix Skill or Category Mandatory / Non-Mandatory Evaluation Focus Conceptual, Logical & Physical Data Modelling Mandatory Strong expertise in designing conceptual, logical, and physical data models aligned with business and enterprise requirements. Capital Markets Domain Knowledge Good to have Deep understanding of trades, instruments, lifecycle events, reference data, and market data concepts. Data Product Modelling Mandatory Experience designing enterprise-scale data products rather than system-specific data models. Data Architecture & Model Design Mandatory Ownership of entity definitions, relationships, keys, constraints, and reusable modelling patterns. Enterprise Data Modelling Tools Mandatory Hands-on expertise with ER/Studio, ERwin, or equivalent data modelling platforms. Business to Data Translation Mandatory Ability to convert business concepts and requirements into scalable and robust data structures. Data Governance & Lineage Mandatory Understanding of governance, lineage, auditability, metadata management, and data quality principles. Stakeholder Collaboration & Communication Mandatory Ability to work effectively with SMEs, business stakeholders, architects, and data engineers while clearly articulating modelling decisions. BigQuery Data Modelling Mandatory Experience designing BigQuery-optimized schemas considering scalability, performance, and cost efficiency. GCP Data Platform Experience Mandatory Experience working within GCP-native data ecosystems and modern cloud data architectures. Analytical & Solution Design Thinking Mandatory Ability to evaluate modelling trade-offs and design fit-for-purpose analytical and operational models. , Regulatory / Surveillance Data Modelling Non-Mandatory Experience modelling regulatory reporting, surveillance, or market abuse data domains. BigQuery Performance Optimization Non-Mandatory Knowledge of denormalization, partitioning, clustering, and perfo

Other Requirements

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