Technical Solutions Architect II -- Data Engineer

World Wide Technology is a leading technology solutions provider, and they are seeking a Technical Solutions Architect II specializing in Data Engineering. The role involves designing and optimizing scalable data platforms, providing technical advisory in cloud data solutions, and leading customers through complex technical challenges.

Responsibilities:

• 10+ years of experience designing, building, and optimizing scalable data platforms, with strength in Snowflake, Databricks and modern Lakehouse architecture
• Deep hands-on experience with modern cloud data platforms, particularly Snowflake and Databricks. This includes platform capabilities such as Snowflake's Snowpark, Dynamic Tables, Streams & Tasks, and Snowflake Cortex, as well as Databricks components such as Lakeflow (Connect, Pipelines, and Jobs), Delta Lake, and Unity Catalog
• Strong data engineering fundamentals: 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 — able to reason through platform tradeoffs and answer architecture-level questions in real time alongside engineering questions, since customers routinely expect both in the same conversation
• Governance fluency: able to represent data quality, security, and trust topics credibly in customer conversations, while governance strategy and roadmap ownership sit with a dedicated specialist role
• Practical understanding of how AI workloads — LLMs, RAG, agentic AI — consume enterprise data. The emphasis is on engineering trusted, scalable data foundations, not building AI models
• Experience integrating and using AI coding assistants and agent tools (e.g., Claude, Copilot, Glean, Snowflake Cortex Code) 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: structuring discovery engagements, identifying technical and organizational gaps, evaluating platform tradeoffs objectively, and delivering actionable recommendations
• Experience supporting a services sales motion in a non-quota-carrying, technical advisory capacity — partnering with account teams to shape and advance service engagements
• Strong communication skills across audiences — data engineers, architects, IT leadership, and executive stakeholders — tailoring technical depth while maintaining credibility with each
• Experience with scoping and/or delivering large-scale data platform migrations
• Experience with additional cloud data platforms such as Google BigQuery, AWS Redshift, or Azure Synapse
• CI/CD, DevOps, and Infrastructure as Code practices for data platforms
• Metadata management, lineage tooling, and data observability/monitoring experience
• Familiarity with dbt, Apache Airflow, Azure Data Factory, Kafka, Event Hubs, or comparable orchestration/integration tools
• Familiarity with enterprise AI platforms — 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

Requirements:

• 10+ years of experience designing, building, and optimizing scalable data platforms, with strength in Snowflake, Databricks and modern Lakehouse architecture
• Deep hands-on experience with modern cloud data platforms, particularly Snowflake and Databricks
• Strong data engineering fundamentals: 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
• Governance fluency: able to represent data quality, security, and trust topics credibly in customer conversations
• Practical understanding of how AI workloads 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 — data engineers, architects, IT leadership, and executive stakeholders
• Experience with scoping and/or delivering large-scale data platform migrations
• Bachelor's degree in computer science, data engineering, or a related field, or equivalent experience
• Active Databricks and/or Snowflake certification(s) highly preferred
• Experience with additional cloud data platforms such as Google BigQuery, AWS Redshift, or Azure Synapse
• CI/CD, DevOps, and Infrastructure as Code practices for data platforms
• Metadata management, lineage tooling, and data observability/monitoring experience
• Familiarity with dbt, Apache Airflow, Azure Data Factory, Kafka, Event Hubs, or comparable orchestration/integration tools
• Familiarity with enterprise AI platforms — 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