Data Solutions Architect

Summary of the Role

Data Solutions Architect to work within a dynamic, remote-first data architecture capability delivering cloud-based data solutions
Responsible for designing and delivering solutions using RDBMS, ETL and ELT, and cloud platforms for blue-chip clients across multiple sectors
Lead cross-functional teams including Data Engineers, Architects, Business Analysts, and QA Analysts in an Agile environment
Own end-to-end technical delivery, stakeholder engagement, and solution quality

Experience and Leadership

• Proven experience in data architecture in a senior or lead role
• Demonstrated experience leading architectural design and strategy for complex data solutions using Snowflake
• Experience overseeing end-to-end delivery of enterprise data platforms
• Background in consulting environments delivering custom data architecture solutions
• Experience within the insurance sector considered an advantage

Architectural Expertise

• Strong expertise in designing and delivering end-to-end data solutions including data warehousing, pipelines, and analytics using Snowflake
• Experience applying Data Mesh and Data Fabric architectural patterns
• Proven ability to develop data product strategies with a product-led mindset
• Extensive experience across cloud platforms including Snowflake, AWS, Azure, and GCP
• Experience integrating Snowflake with cloud services and big data tools
• Strong understanding of cloud infrastructure and its impact on data architecture

Data Technology Skills

• Deep hands-on experience with Snowflake features, capabilities, and best practices
• Strong understanding of data modelling principles and techniques
• Solid knowledge of big data technologies such as Apache Spark
• Working knowledge of Hadoop ecosystems
• Experience with programming languages such as Python, R, or Java
• Knowledge of ETL and ELT processes including DBT
• Experience with SQL and NoSQL databases
• Exposure to data visualisation tools and DevOps principles and tools
• Familiarity with machine learning and AI concepts and their integration into data architectures

Design and Lifecycle Management

• Proven experience designing modern, scalable, and resilient data architectures
• Strong understanding of the full data architecture lifecycle from concept to deployment and consumption

Data Management and Governance

• Strong knowledge of data management principles and best practices
• Experience implementing data governance frameworks
• Understanding of data security and compliance requirements including GDPR, CCPA, HIPAA, or similar regulations