Functional Data Architect

Encourage everyone to have a voice and invite opinions from all, including quieter members of the team.

Deal effectively with ambiguous and unstructured problems and situations.

Initiate open and candid coaching conversations at all levels.

Go to person

Move easily between big picture thinking and managing relevant detail.

Anticipate stakeholder needs, and develop and discuss potential solutions, even before the stakeholder realizes they are required.

Contribute technical knowledge in area of specialism.

Contribute to an environment where people and technology thrive together to accomplish more than they could apart.

Navigate the complexities of cross-border and/or diverse teams and engagements.

Initiate and lead open conversations with teams, clients and stakeholders to build trust.

Uphold the firm's code of ethics and business conduct.

Design and deliver enterprise and solution data architectures that solve business problems and enable analytics, reporting, and regulatory outcomes.

Define and govern data models, standards, and best practices across conceptual, logical, and physical layers.

Lead data analysis activities, including source system analysis, data profiling, and source-to-target mapping definitions.

Develop and review data models and canonical data definitions; assure model alignment to business capabilities and use cases.

Establish and embed data governance and data quality practices, policies, and controls, including measurement, monitoring, and remediation.

Partner with business stakeholders to translate requirements into scalable data solutions and roadmaps; articulate trade-offs and options.

Oversee non-functional requirements (scalability, performance, security, reliability) and align architecture to target-state principles.

Provide architecture oversight through delivery, ensuring traceability from requirements to design to implementation.

Contribute to reference architectures and reusable patterns (ingestion, curation, access) to accelerate delivery.

More than 10 years of experience in Financial Services centered around data platforms

Experienced in Financial Services, with deep expertise in Banking, Insurance and / or Asset & Wealthdata domains welcomed.

Understanding of work involved in delivering a data platform: Source system analysis,dataprofiling,creating source to target mapping and others

Solid understanding of technology data platform components:Ingestion,Metadata driven pipeline, DQ service, data architecture types e.g. medallion, data mesh etc.

Data analysis and profiling; source-to-target mapping; data modeling across conceptual, logical, and physical layers.

ETL/ELT and integration patterns; batch and streaming data processing.

Data warehousing approaches; relational and analytical data stores.

Cloud technologies (MS Azure, Databricks, AWS); metadata and lineage; data quality management and controls.

Results oriented and self-starter

Superior attention to detail

Ability to multitask and work under pressure

Good analytical and communication skills

Strong work ethics

Proficiency in English

Committed and responsible