Technical Solutions Architect II - Data Engineer

About World Wide Technology

World Wide Technology (WWT), established in 1990, combines strategic insight, deep technical expertise, and premier partnerships to assist public and private sectors in designing, developing, and scaling AI, digital, cybersecurity, cloud, and infrastructure solutions. Operating through its Advanced Technology Center, WWT offers a collaborative ecosystem with cutting-edge hardware and software, enabling clients to prototype, test, validate, and deploy technology solutions globally. With over 14,000 employees across 60+ locations worldwide, WWT is acknowledged by Fortune® and Great Place to Work for fostering innovation, trust, and an exceptional work environment. WWT serves large enterprises and sectors in more than 130 countries, with Softchoice supporting commercial and SMB markets in North America.

Role Overview

The AI & Data Solutions team serves as a pre-sales advisory function within WWT’s GS&A organization, guiding organizations from AI curiosity to impactful applications. The Technical Solutions Architect II focuses on data engineering, bringing extensive hands-on expertise with data platforms to customer discussions, simplifying complex technical details to actionable business decisions. This role collaborates with account teams throughout the entire sales cycle to translate insights into services opportunities for WWT.

Key Responsibilities

• Lead pre-sales engagements independently, including workshops, discovery sessions, architecture reviews, and briefings, concentrating on preparing data for AI readiness and mapping the journey from data foundation to AI value.
• Advance opportunities involving AI Studio, AI Foundry, and AI Factory offerings, emphasizing data strategies, engineering maturity, and AI-ready architectures.
• Communicate intricate technical concepts in a manner that aligns with business and executive perspectives, linking technology directly to desired outcomes.
• Create and contribute technical content such as whitepapers, workshop materials, and internal training to document effective AI-ready data approaches.
• Engage with WWT’s AI Proving Ground and partner ecosystem, particularly technologies like Databricks and Snowflake, to develop insights, validate approaches, and enable field activities.

Required Expertise

• Over 10 years of experience designing and optimizing scalable data platforms, with strong expertise in Snowflake, Databricks, and lakehouse architectures.
• Hands-on proficiency with modern cloud data platforms, including Snowflake capabilities like Snowpark and Streams & Tasks, and Databricks components such as Lakeflow, Delta Lake, and Unity Catalog.
• Solid fundamentals in data engineering, including ETL/ELT pipeline creation, data orchestration, workflow automation, batch and streaming data processing, and data modeling for analytics and operations.
• Proficient in SQL and Python to independently author, debug, and review production-grade code.
• Deep understanding of lakehouse and data platform architectures, able to deliberate tradeoffs and answer both architectural and engineering queries in real-time during customer interactions.
• Competency in governance topics like data quality, security, and trust, contributing credibly to customer discussions.
• Practical knowledge of how AI workloads such as Large Language Models, Retrieval-Augmented Generation, and agentic AI consume enterprise data, focusing on building scalable, reliable data foundations rather than AI model development.
• Experience utilizing AI coding assistants and agent tools such as Claude, Copilot, Glean, and Snowflake Cortex Code with cloud data platforms.
• Experience deploying Databricks and Snowflake on public clouds including Azure, AWS, or Google Cloud Platform.
• Advisory skills to guide customers through ambiguous technical challenges, structuring discovery, diagnosing gaps, assessing platform tradeoffs objectively, and providing clear recommendations.
• Proven record supporting a services sales process in a technical advisory, non-quota role, collaborating with account teams to progress service engagements.
• Strong communication abilities adaptable to varied audiences including data engineers, architects, IT leadership, and executives, maintaining technical credibility throughout.
• Experience with planning or executing large-scale migrations of data platforms.

Preferred Qualifications

• Familiarity with other cloud data platforms like Google BigQuery, AWS Redshift, or Azure Synapse.
• Knowledge of CI/CD, DevOps, and Infrastructure as Code practices tailored to data platforms.
• Experience with metadata management, data lineage tools, and data monitoring or observability.
• Familiarity with orchestration and integration tools such as dbt, Apache Airflow, Azure Data Factory, Kafka, or Event Hubs.
• Experience with enterprise AI platforms including Azure AI, AWS SageMaker, Google Vertex AI, Databricks Mosaic AI, or NVIDIA NIM.
• A passion for enabling clients to solve complex business challenges through advanced data engineering and trustworthy data foundations.

Education & Certifications

Bachelor’s degree in computer science, data engineering, or a related discipline or equivalent practical experience is required. Active certifications with Databricks and/or Snowflake are highly preferred.

Employee Benefits

• Health & Wellbeing: Combined Health Insurance, Employee Assistance Program, and Wellness programs.
• Financial Benefits: Competitive salary, profit sharing, life and disability insurance, and tuition reimbursement.
• Paid Time Off: Paid vacation, holidays, parental leave, sick leave, and bereavement leave.

Our Culture

WWT commits to fostering an empowering environment where employee success is based on skills, performance, and dedication. The company promotes a culture of inclusion, innovation, collaboration, and respect, ensuring it remains an outstanding workplace for all team members around the world.