At a glance
- Experience
- 6+ years experience
- Location
- London · Europe
About the role
- As a Data Solutions Architect at Spaulding Ridge, you will lead the strategy, architecture and delivery of enterprise-scale data and analytics solutions for clients.
- You will work across data architecture, software engineering, cloud platforms, analytics engineering and client advisory to translate business priorities into secure, scalable solutions.
- This role provides technical leadership across multiple projects and teams, mentoring engineers and acting as a trusted adviser.
Responsibilities
- Lead the design and governance of modern data warehouses, data lakes, lakehouse platforms, semantic layers, dimensional models, master data strategies and analytics ecosystems.
- Architect cloud-native data platforms—particularly Snowflake—covering performance, workload management, security, access controls, cost governance, multi-environment deployment, data sharing, replication and disaster recovery.
- Define scalable batch, real-time, event-driven, API, orchestration and ELT/ETL integration patterns using modern data integration technologies.
- Establish standards for analytics engineering, dbt, the modern data stack, DataOps, testing, documentation, CI/CD, Infrastructure as Code, observability and automated deployment.
- Embed metadata, lineage, privacy, security, regulatory compliance, monitoring and data quality controls into platform and data product designs.
- Lead technical workstreams, mentor engineers, prepare estimates and technical proposals, and deliver client presentations, executive briefings, architecture reviews and workshops.
Requirements
- 6+ years’ experience in data and analytics, including the design and delivery of enterprise-scale data platforms and analytics solutions.
- Proven success in leading technical workstreams, mentoring engineers and driving architectural decisions across multiple projects and teams.
- Ability to align architecture with business strategy, define data roadmaps with executive and cross-functional stakeholders, and translate requirements into scalable solutions.
- Experience in pre-sales, solution estimation, technical proposal development and client-facing presentations.
- Deep expertise in modern data architectures, including data warehouses, data lakes, lakehouse platforms and analytics ecosystems.
- Extensive experience in enterprise and dimensional data modelling, semantic layers, master data strategies and data governance frameworks.
- Advanced experience in designing and operating cloud-native data platforms, particularly Snowflake, including performance and workload management, security and access controls, cost governance and FinOps, multi-environment deployments, data sharing, replication and disaster recovery.
- Expertise in scalable enterprise ELT/ETL, data integration, real-time and batch processing, event-driven systems, APIs and orchestration patterns.
- Advanced experience with dbt and enterprise-scale modern data stack architectures, including framework design, governance, testing, documentation and deployment standards.
- Strong software engineering background, with proficiency in Python and SQL and knowledge of architectural principles, design patterns, testing frameworks and engineering best practices.
Preferred qualifications
- Experience with BigQuery, Databricks, Synapse, Redshift or similar platforms is highly desirable.
Workplace
- Travel may be required for client engagements, workshops, key stakeholder meetings and internal team events.
Skills
- Snowflake
- Azure
- Google Cloud Platform
- BigQuery
- Databricks
- Synapse
- Redshift
- Fivetran
- Workato
- Boomi
- Airbyte
- Dbt
Show all 15 skills
- Python
- SQL
- Terraform
