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# Data Architect (Snowflake)

- **Company:** AND Digital
- **Location:** London, United Kingdom
- **Salary:** £90,119
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Data Analysis, Cloud Engineering, Data Architecture, Data Governance, Extract Transform Load (ETL), Data Sharing, Data Structures, Data Stores, Data Systems, Distributed Systems, Fault Tolerance, Indexed Sequential Access Method (ISAM), Metadata, NoSQL, Oracle (Applications), Performance Tuning, Software Tools, SQL Databases, Data Streaming, Data Processing, File Transfer Protocol (FTP), Data Ingestion, Snowflake, Sybase, Data Strategy, Apache Kafka, Domain Driven Design, Microservices
- **Published:** November 13, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5963541276

## About the Role

We are seeking an experienced Data Architect with deep expertise in Snowflake to define, design and govern our enterprise data architecture. The role will lead the development of scalable, secure, cost-effective and high-performing data solutions that enable business intelligence, advanced analytics, data science and AI-driven use cases., * UK wealth management, financial services or fintech experience; candidates from other complex, regulated industries will also be considered.

 * Experience working with DBT & Dagster
 * Legacy modernisation experience involving Oracle, Sybase, ISAM storage and SFTP/file-based integration, including migration, coexistence, reconciliation, CDC and progressive decoupling.

## Description

* Data Architecture & Strategy: Define and evolve data strategy, architecture principles, standards and target-state roadmaps, balancing scalability, resilience, security, cost and delivery speed.
 * Snowflake Platform Architect: Design and govern scalable, secure and cost-effective Snowflake architectures, covering data ingestion, transformation, modelling, performance optimisation, workload management, data sharing and integration to support enterprise analytics and AI use cases.
 * Cloud-Native & Distributed Systems: Deep expertise in microservices, domain-driven design (DDD), bounded contexts, data ownership, event-driven integration, eventual consistency and distributed transactions.
 * Event Streaming: Hands-on experience designing and operating Kafka, Kinesis or equivalent platforms, including partitioning, ordering, event contracts, schema evolution, idempotency, replay, delivery guarantees, fault tolerance, security and operational support.
 * Data Modelling & Storage: Strong data modelling skills and the ability to select appropriate data stores-including relational, NoSQL, graph, time-series, distributed SQL and lakehouse technologies-based on business and technical requirements. Experienced in designing and developing semantic data models using tools such as dbt, ensuring consistent business definitions, reusable data structures, and reliable data for reporting and analytics.
 * End-to-End Data Flows: Architect operational and analytical data pipelines across APIs, streaming, CDC, batch and ETL/ELT, embedding data quality, lineage, metadata, security, testing and observability throughout.
 * Technical Leadership & Delivery: Work closely with engineering and product teams in fast-paced agile environments, making pragmatic trade-offs and establishing lightweight guardrails, automation and architecture decision records.
 * Risk, Security & Resilience: Design secure, well-governed cloud data architectures that support sensitive data handling, operational resilience, traceable controls and regulatory obligations.
 * AI-Assisted Engineering: Practical experimentation with AI-assisted architecture and engineering tools, understanding their benefits and limitations across research, modelling, coding, testing and documentation., We champion tech that helps people work smarter, but we want to get to know you! If you use AI to assist with your application or interview prep, please ensure all information submitted remains an accurate, truthful representation of your personal achievements and capabilities rather than generating false or misleading information. We may reject applications where AI is used inappropriately at any stage of the recruitment process.