Role Purpose

Building data solutions is a cornerstone of the data strategy. The purpose of this role is to identify and map data sources, design the underlying data models and transformation logic, and support the design and building of data solutions as part of projects and BAU (Business as Usual) activities. The Data Architect will define and govern the organisation's data architecture — mapping the current (as-is) data landscape, designing the target (to-be) landscape, and guiding the analysis and integration of data sources feeding into the enterprise. The role bridges strategy and delivery: translating business and technology needs into coherent data architectures, master data structures, and reusable data capabilities that data engineering and solution teams can build against.

Key Responsibilities

- Document and maintain the current-state data landscape: systems, data flows, integration points, and how data moves across the organization.
- Design the target-state data landscape aligned to business strategy and future data needs, and produce roadmaps and transition plans (gap analysis) from current to target state.
- Identify and catalogue data sources (internal systems, external feeds, APIs, third-party data) relevant to a given business or solution need, mapping source structures to target models and tracing data lineage from source through to consumption.
- Design the transformation logic required to move data from source structures into target models, including mapping rules, business logic and calculations.
- Produce and maintain conceptual, logical and physical data models across source, integration and consumption layers, applying appropriate modelling standards (e.g. dimensional modelling).
- Define the master data model(s) (e.g. customer, product, supplier, location) and rules for creation, stewardship and lifecycle management, working with data governance teams on golden-record strategies and data quality standards.
- Design and support the build of data-heavy solutions, including those delivered on the data platform,



translating business requirements into practical, well-modelled data solutions.
- Work hands-on with delivery teams through design, build and testing to ensure solutions match the intended architecture and data models, defining what is sourced, how it's transformed, where it lands and how it's consumed.
- Contribute to data architecture designs and standards in support of projects and programmes, and participate in design reviews to assure alignment with the target landscape.
- Ensure knowledge and best practices are transferred to colleagues via mentoring, knowledge sharing sessions and participation in the Data Community.

Experience

- Bachelor's degree in business, computer science, computer engineering, electrical engineering, system analysis or a related field of study, or equivalent experience
- Expert in conceptual, logical and physical data modelling
- Significant experience identifying and mapping data sources, and designing source-to-target transformation logic
- Proven experience designing and building data solutions, including data-heavy solutions delivered on a data platform
- Broad experience in data standardisation procedures and best practices
- Significant experience designing, implementing and supporting data management solutions across Master Data, Meta Data and Reference Data domains
- Experience in data cleansing and maintenance techniques for the data life-cycle
- Ability to work independently within a high performing team
- Knowledge of business models, operating models, financial models, cost-benefit analysis, budgeting and risk management
- Knowledge of data modelling techniques including dimensional modelling
- Knowledge of data modelling tools e.g. ERwin




- Ability to query and analyse data using SQL or Python
- Knowledge of data mapping and transformation approaches, and data lineage documentation
- Knowledge of data cataloguing concepts and tools e.g. Microsoft Purview
- Familiarity with data warehouse, data lake and data mesh architectural concepts, sufficient to design solutions that fit them
- Familiarity with information management practices, system development life cycle management, and EA frameworks
- Knowledge of analytics, data visualisation, predictive analytics, data science and AI
- Knowledge of handling sensitive data (GDPR, PII etc.)
- Exceptional soft and interpersonal skills, including teamwork, facilitation and negotiation, with an ability to work with individuals at all levels within the organization
- Excellent problem solving, analytical and technical skills
- Excellent written, verbal, communication and presentation skills
- Excellent planning and organisational skills

Performance Indicators

- Personal and company objectives for the year are met
- Successful delivery of projects and tasks within agreed timescales
- Data sources correctly identified, mapped and validated before solution build begins, with a low rate of late-discovered source issues
- Transformation and data models are clear, reusable and require minimal rework during build/test
- Creation of data architecture and mapping artefacts that can be easily consumed by business stakeholders
- Data solutions, including data-heavy platform solutions, delivered in line with agreed models and architecture, with a low defect/rework rate
- Master data quality (completeness, accuracy, duplication rate) improves against baseline
- Have a valuable understanding of the data landscape and can identify opportunities to improve data management
- Promotes collaborative technologies, processes and behaviours to facilitate sharing of ideas and work-knowledge.
- Be familiar with data platform technologies such as Fabric, Synapse etc

📌 Data Architect (India)
🏢 Black Piano
📍 India