Data Solution Architect
Location: Remote
Direct client
About the Role
· We are seeking experienced Data Solution Architect to support the design and
· evolution of enterprise solution architecture and data products for the OneData platform.
· Working within the Enterprise Architecture team, you will design scalable data architectures, enterprise data models, and modern data engineering solutions
that enable trusted, governed, and reusable data across the organization.
· Your primary focus will be on enterprise data architecture, dimensional and relational data modelling, DBT engineering patterns, Medallion Architecture, and structured and unstructured data solutions on Databricks.
· You will define reusable architecture and engineering standards and guide delivery teams in translating those standards into scalable data products.
· You will work closely with HUB & SPOKE delivery teams to translate business and data
· requirements into ERDs, data models, data flows, transformation designs, and
· implementation patterns, enabling teams to independently build high-quality data
· products aligned with the OneData platform.
Qualifications
· 12+ years of experience in enterprise data architecture, solution architecture, data engineering, or modern cloud data platforms.
· Strong hands-on experience with Databricks, DBT, Unity Catalog, SQL, and Python.
· Deep expertise in data architecture and data modelling, including dimensional modelling, star schemas, fact/dimension design, normalization/denormalization, business and surrogate keys, SCD patterns, and data product design.
· Strong understanding of Medallion Architecture and the design of scalable enterprise data layers.
· Demonstrated experience designing and implementing DBT-based data transformation frameworks, reusable engineering patterns, testing, documentation, and deployment practices.
· Experience designing data architectures for structured, semi-structured, and unstructured data.
· Experience with modern data formats and storage patterns such as Delta Lake, JSON, Parquet, documents/files, and object storage.
· Strong understanding of data integration, ingestion, transformation, data quality, metadata, lineage, governance, and performance optimization.
· Ability to translate business requirements into logical and physical data models, ERDs, solution architectures, and detailed engineering designs.
· Experience designing scalable architectures that support downstream analytics, reporting, data science, and other enterprise consumption patterns.
· Strong stakeholder management and technical leadership skills, with the ability to guide engineering teams and challenge designs when they do not align with enterprise standards.