Data Solutions Architect

Spaulding Ridge is an advisory and IT implementation firm. We help global organizations get financial clarity into the complex, daily sales, and operational decisions that impact profitable revenue generations, efficient operational performance, and reliable financial management.

As a Data Solutions Architect, you will lead the strategy, architecture and delivery of enterprise-scale data and analytics solutions for our clients. Working across data architecture, software engineering, cloud platforms, analytics engineering and client advisory, you will translate business priorities into secure, scalable, well-governed and cost-effective solutions.

You will partner with executive stakeholders, business leaders and technical teams to define data roadmaps and target-state architectures, evaluate technology options and guide delivery from proposal and estimation through to implementation, enablement and support. You will help clients modernise fragmented data environments and establish trusted data products, intuitive analytics experiences and reusable engineering capabilities that deliver measurable business value.

This role also provides technical leadership across multiple projects and teams. You will mentor engineers, facilitate architecture reviews and technical workshops, establish standards and best practices, and act as a trusted adviser who can challenge assumptions, identify opportunities and influence strategic decisions.

• 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.

Travel may be required for client engagements, workshops, key stakeholder meetings and internal team events.

• 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.
• Strong understanding of data product thinking and the creation of scalable, reusable and business-oriented models, standards and development 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.
• Strong knowledge of Azure and/or Google Cloud Platform services across data, storage, networking, security and monitoring.
• Experience with BigQuery, Databricks, Synapse, Redshift or similar platforms is highly desirable.
• Expertise in scalable enterprise ELT/ETL, data integration, real-time and batch processing, event-driven systems, APIs and orchestration patterns.
• Experience with Fivetran, Workato, Boomi, Airbyte or similar integration platforms.
• Ability to evaluate technology options and define target-state architectures based on business and technical requirements.
• Advanced experience with dbt and enterprise-scale modern data stack architectures, including framework design, governance, testing, documentation and deployment standards.
• Ability to establish DataOps practices that improve automation, quality and observability across data pipelines.
• Strong software engineering background, with proficiency in Python and SQL and knowledge of architectural principles, design patterns, testing frameworks and engineering best practices.
• Experience with CI/CD, automated deployment and Infrastructure as Code, preferably Terraform.
• Experience in defining engineering standards and driving operational excellence across data platforms.
• Strong understanding of data governance, metadata management, lineage, privacy, security and regulatory compliance.
• Experience in defining policies, enterprise data quality controls, observability solutions and monitoring frameworks that support reliable, trusted and well-governed data assets.
• Strong consulting mindset, with the ability to challenge requirements, identify opportunities and propose innovative solutions.
• Excellent communication and presentation skills, with experience delivering architecture reviews, executive briefings and technical workshops, and building trusted adviser relationships that influence strategic decisions.