Job Summary

Data Architect – Financial Services

Must-Have and Nice-to-Have Skills

Must-Have Skills

• Enterprise data architecture: Strong experience designing and governing enterprise data architectures for large, complex systems.
• Data modelling: Proven ability to create domain, conceptual, logical, and physical data models.
• Architecture patterns: Strong knowledge of domain-driven design and CQRS implementation.
• Relational databases: Deep expertise in data design and modelling using Oracle and PostgreSQL.
• Data design fundamentals: Strong understanding of normalization, denormalization, OLTP systems, transactional data models, and scalable data structures.
• Distributed data design: Solid understanding of distributed database architecture, scalability, resiliency, performance, and disaster-recovery considerations.
• Architecture analysis: Ability to assess current-state and target-state architectures and recommend modernization or optimization opportunities.
• Integration and governance: Strong knowledge of enterprise integration patterns, data governance principles, and architecture governance.
• Transformation planning: Experience supporting data migration, integration, and transformation planning.
• Stakeholder collaboration: Ability to work with business stakeholders, architects, application teams, development teams, infrastructure teams, and engineering leads.
• Communication and documentation: Excellent written and verbal English, presentation skills, architecture documentation, and the ability to explain complex concepts to technical and non-technical audiences.
• Problem solving and delivery: Strong analytical skills, independent working ability, and a collaborative approach in fast-paced enterprise environments.
• Financial-services domain: Experience in financial services, capital markets, investment banking, trading platforms, risk, regulatory, or comparable transactional environments.

Nice-to-Have Skills

• NoSQL and distributed databases: Hands-on experience with Cassandra and YugabyteDB; familiarity with GCP Spanner or comparable distributed platforms.
• Data modelling tools: Experience with ER/Studio and Hackolade.
• Cloud and hybrid architecture: Familiarity with cloud and hybrid data architectures.
• Financial data knowledge: Strong understanding of financial data domains and complex transactional systems.
• Enterprise transformation: Experience working on large-scale enterprise transformation programmes.
• Governance frameworks: Exposure to formal data-governance and enterprise-architecture frameworks.
• Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related discipline.
• Certifications: Financial-industry or architecture certifications.

Key Responsibilities

Data Architect – Financial Services

Must-Have and Nice-to-Have Skills

Must-Have Skills

• Enterprise data architecture: Strong experience designing and governing enterprise data architectures for large, complex systems.
• Data modelling: Proven ability to create domain, conceptual, logical, and physical data models.
• Architecture patterns: Strong knowledge of domain-driven design and CQRS implementation.
• Relational databases: Deep expertise in data design and modelling using Oracle and PostgreSQL.
• Data design fundamentals: Strong understanding of normalization, denormalization, OLTP systems, transactional data models, and scalable data structures.
• Distributed data design: Solid understanding of distributed database architecture, scalability, resiliency, performance, and disaster-recovery considerations.
• Architecture analysis: Ability to assess current-state and target-state architectures and recommend modernization or optimization opportunities.
• Integration and governance: Strong knowledge of enterprise integration patterns, data governance principles, and architecture governance.
• Transformation planning: Experience supporting data migration, integration, and transformation planning.
• Stakeholder collaboration: Ability to work with business stakeholders, architects, application teams, development teams, infrastructure teams, and engineering leads.
• Communication and documentation: Excellent written and verbal English, presentation skills, architecture documentation, and the ability to explain complex concepts to technical and non-technical audiences.
• Problem solving and delivery: Strong analytical skills, independent working ability, and a collaborative approach in fast-paced enterprise environments.
• Financial-services domain: Experience in financial services, capital markets, investment banking, trading platforms, risk, regulatory, or comparable transactional environments.

Nice-to-Have Skills

• NoSQL and distributed databases: Hands-on experience with Cassandra and YugabyteDB; familiarity with GCP Spanner or comparable distributed platforms.
• Data modelling tools: Experience with ER/Studio and Hackolade.
• Cloud and hybrid architecture: Familiarity with cloud and hybrid data architectures.
• Financial data knowledge: Strong understanding of financial data domains and complex transactional systems.
• Enterprise transformation: Experience working on large-scale enterprise transformation programmes.
• Governance frameworks: Exposure to formal data-governance and enterprise-architecture frameworks.
• Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related discipline.
• Certifications: Financial-industry or architecture certifications.

Skill Requirements

Data Architect – Financial Services

Must-Have and Nice-to-Have Skills

Must-Have Skills

• Enterprise data architecture: Strong experience designing and governing enterprise data architectures for large, complex systems.
• Data modelling: Proven ability to create domain, conceptual, logical, and physical data models.
• Architecture patterns: Strong knowledge of domain-driven design and CQRS implementation.
• Relational databases: Deep expertise in data design and modelling using Oracle and PostgreSQL.
• Data design fundamentals: Strong understanding of normalization, denormalization, OLTP systems, transactional data models, and scalable data structures.
• Distributed data design: Solid understanding of distributed database architecture, scalability, resiliency, performance, and disaster-recovery considerations.
• Architecture analysis: Ability to assess current-state and target-state architectures and recommend modernization or optimization opportunities.
• Integration and governance: Strong knowledge of enterprise integration patterns, data governance principles, and architecture governance.
• Transformation planning: Experience supporting data migration, integration, and transformation planning.
• Stakeholder collaboration: Ability to work with business stakeholders, architects, application teams, development teams, infrastructure teams, and engineering leads.
• Communication and documentation: Excellent written and verbal English, presentation skills, architecture documentation, and the ability to explain complex concepts to technical and non-technical audiences.
• Problem solving and delivery: Strong analytical skills, independent working ability, and a collaborative approach in fast-paced enterprise environments.
• Financial-services domain: Experience in financial services, capital markets, investment banking, trading platforms, risk, regulatory, or comparable transactional environments.

Nice-to-Have Skills

• NoSQL and distributed databases: Hands-on experience with Cassandra and YugabyteDB; familiarity with GCP Spanner or comparable distributed platforms.
• Data modelling tools: Experience with ER/Studio and Hackolade.
• Cloud and hybrid architecture: Familiarity with cloud and hybrid data architectures.
• Financial data knowledge: Strong understanding of financial data domains and complex transactional systems.
• Enterprise transformation: Experience working on large-scale enterprise transformation programmes.
• Governance frameworks: Exposure to formal data-governance and enterprise-architecture frameworks.
• Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related discipline.
• Certifications: Financial-industry or architecture certifications.

Other Requirements