Technical Solutions Architect
Summary
Technical Solutions Architect designing and optimizing scalable data platforms with Snowflake, Databricks, and lakehouse architectures in a pre-sales/consulting capacity.
Salary: £62,000 - 102,000 per year
Requirements:- 10+ years of experience designing, building, and optimizing scalable data platforms, with strength in Snowflake, Databricks, and modern lakehouse architecture.
- Prior experience in a pre-sales, consulting, solutions engineering, or technical advisory capacity within an enterprise technology organization is preferred.
- Deep hands-on experience with modern cloud data platforms, particularly Snowflake and Databricks.
- Experience with platform capabilities such as Snowflake Snowpark, Dynamic Tables, Streams & Tasks, and Snowflake Cortex.
- Experience with Databricks components such as Lakeflow (Connect, Pipelines, and Jobs), Delta Lake, and Unity Catalog.
- Strong data engineering fundamentals, including ETL/ELT pipeline design and implementation, data orchestration and workflow automation, batch and streaming processing, and data modeling for analytical and operational workloads.
- Proficiency in SQL and Python sufficient to write, debug, and review production-quality code independently.
- Working fluency in lakehouse and data platform architecture, including the ability to reason through platform tradeoffs and answer architecture-level questions in real time.
- Governance fluency, with the ability to represent data quality, security, and trust topics credibly in customer conversations.
- Practical understanding of how AI workloads such as LLMs, RAG, and agentic AI consume enterprise data.
- Experience integrating and using AI coding assistants and agent tools with cloud data platforms.
- Experience implementing Databricks and Snowflake solutions on Azure, AWS, or Google Cloud.
- Advisory mindset and the ability to lead customers through ambiguous technical challenges.
- Experience supporting a services sales motion in a non-quota-carrying, technical advisory capacity.
- Strong communication skills across audiences, including data engineers, architects, IT leadership, and executive stakeholders.
- Experience with scoping and/or delivering large-scale data platform migrations.
- Bachelors degree in computer science, data engineering, or a related field, or equivalent experience.
- Active Databricks and/or Snowflake certification(s) are highly preferred.
- Preferred experience with additional cloud data platforms such as Google BigQuery, AWS Redshift, or Azure Synapse.
- Preferred experience with CI/CD, DevOps, and Infrastructure as Code practices for data platforms.
- Preferred experience with metadata management, lineage tooling, and data observability/monitoring.
- Preferred familiarity with dbt, Apache Airflow, Azure Data Factory, Kafka, Event Hubs, or comparable orchestration/integration tools.
- Preferred familiarity with enterprise AI platforms such as Azure AI, AWS SageMaker, Google Vertex AI, Databricks Mosaic AI, NVIDIA NIM, or similar.
- A passion for helping customers solve complex business problems through modern data engineering and trusted data foundations.
- Independently lead pre-sales enterprise customer engagements, including workshops, discovery sessions, architecture reviews, and executive briefings, focusing on data readiness for AI and the practical path from data foundation to AI value.
- Advance opportunities across the AI Studio, AI Foundry, and AI Factory offerings, with particular emphasis on data strategy, data engineering maturity, and AI-ready data architecture.
- Translate complex technical concepts into language that resonates with business and executive stakeholders by connecting technology directly to outcomes.
- Author and contribute technical content such as whitepapers, workshop curriculum, and internal enablement that document field-tested approaches for AI-ready data.
- Engage with our AI Proving Ground and partner ecosystems, particularly Databricks and Snowflake, to develop insights, validate approaches, and support field enablement.
- Partner with account teams across the full sales cycle, converting technical clarity into services opportunities.
- Agentic AI
- AI
- Airflow
- AWS
- Redshift
- Architect
- Azure
- BigQuery
- CI/CD
- Cloud
- Databricks
- DevOps
- ETL
- Support
- Kafka
- Python
- RAG
- SQL
- Security
- Snowflake
- Unity
- dbt
- GameDev
- Copilot
- Hardware
- SMB
More:
We are World Wide Technology (WWT), a global technology organization founded in 1990 that helps public and private sector clients design, build, and scale intelligent AI, digital, cybersecurity, cloud, and infrastructure solutions. Our AI & Data Solutions team operates as a pre-sales advisory practice within our GS&A organization, helping organizations move from AI interest to AI impact. This is a full-time, salaried Technical Solutions Architect role focused on data engineering and AI-ready data foundations, based in London. We offer a challenging and rewarding position in a growing, truly international environment, with a competitive salary, bonus opportunities, and benefits. We also promote equal opportunities and a culture of belonging, innovation, collaboration, and respect across our global team.
last updated 35 week of 2026