Technical Solutions Architect II -- Data Engineer

World Wide Technology (WWT) is hiring a Technical Solutions Architect II – Data Engineer for its AI & Data Solutions presales advisory practice. The role helps customers prepare enterprise data for AI by advising on data readiness, bridging data engineering and data science, supporting sales opportunities, and translating technical recommendations for business and executive stakeholders.

Responsibilities

• Presales Engagement: Join account teams in customer meetings across the United States, delivering briefings, workshops, discovery sessions, and architecture reviews. Support account teams as a trusted guest in their accounts, bringing technical credibility and business clarity to each conversation
• AI Data Readiness Advisory: Guide customers through getting their data ready for AI, including data pipelines for AI workloads, analytics readiness, data quality, and the practical path from data foundation to AI value
• Data Engineering and Data Science Bridge: Serve as the subject matter expert across both disciplines. Hold peer level conversations with customer data engineers and data scientists, and help each side understand what the other needs from the data
• Opportunity Support: Support opportunities across the AI Studio, AI Foundry, and AI Factory offerings, qualifying services opportunities and handing them off to the appropriate services teams
• Messaging and Content: Build customer briefings and develop messaging aligned to what customers care about most, and contribute to team thought leadership and internal enablement content
• Business Translation: Translate complex technical concepts into language that resonates with business and executive stakeholders by connecting technology directly to outcomes
• Partner Ecosystem Engagement: Engage with WWT’s AI Proving Ground and partner ecosystems, particularly Databricks and Snowflake, along with Microsoft Fabric, to develop insights, validate approaches, and support field enablement
• Global Team Collaboration: Help the team scale globally by sharing customer insight, assets, demos, and best practices with colleagues around the world. Support opportunities outside the US from time to time as needed

Preferred

• Hands on experience with Snowflake and/or Databricks is highly desirable, as most customers we meet use one or both
• Exposure to Microsoft Fabric and similar modern data platforms is also relevant
• Active Databricks and/or Snowflake certification(s) highly preferred
• Snowflake
• Databricks
• Microsoft Fabric
• Modern Data Platforms
• Databricks Certification
• Snowflake Certification

Benefits

• Remote position located within the US
• Health (Medical & Prescription), Dental, and Vision Care
• Onsite Health Centers (MO & IL)
• Employee Assistance Program
• Wellness program
• Profit Sharing
• 401k Plan with Company Matching
• Life and Disability Insurance
• Flexible Spending Accounts
• Tuition Reimbursement
• PTO & Holidays
• Parental Leave
• Medical Leave
• Military Leave
• Bereavement
• Day of Caring
• Family Planning Benefits
• Nursing Mothers Benefits
• Voluntary Legal
• Voluntary Supplemental Accident/Illness/Hospital
• Voluntary ID Theft
• Pet Insurance
• Employee Discount Program

Company

• Technology services for digital transformation and IT modernization
• Maryland Heights, Missouri, USA
• http://www.wwt.com/
• Founded in 1990
• 10001+ employees

Qualifications

• A minimum of 3 years of relevant technical experience across data engineering and data science, including hands on experience preparing and managing data for data science use cases
• Customer facing sales experience is required, gained in a presales, consulting, solutions engineering, reseller, or systems integrator setting
• The ideal candidate is a data scientist who has had to prepare and manage their own data, or a data engineer who has worked closely with data scientists and understands their needs
• Data engineering fundamentals, including data ingestion and integration, ETL and ELT pipeline design, orchestration, batch and streaming processing, SQL, Python, and Apache Spark, data modeling, data quality and observability, and metadata and lineage
• Working data science experience, including feature engineering, model development and evaluation, and experimentation
• The requirement is enough depth to hold credible peer conversations with customer data scientists and to understand what they need from data platforms
• Practical understanding of how AI workloads, including large language models (LLMs), retrieval augmented generation (RAG), and agentic AI, consume enterprise data
• Cloud familiarity from a data and AI perspective, including the ability to move and use data from AWS, Azure, or Google Cloud environments in AI initiatives
• Working knowledge of enterprise data governance, security, and data strategy, and how trusted data enables successful AI initiatives
• Strong communication skills, with the ability to speak with data engineers, data scientists, architects, developers, IT leadership, and executive stakeholders, tailoring technical depth appropriately while maintaining credibility with every audience
• Advisory mindset and the ability to lead customers through ambiguous technical challenges, structure discovery conversations, identify gaps, evaluate platform tradeoffs objectively, and deliver actionable recommendations
• Sales experience and commercial awareness to support account teams effectively in fast moving sales cycles, including working as a guest in accounts owned by others
• Genuine curiosity and a habit of staying current
• Familiarity with complementary technologies such as dbt, Apache Airflow, Azure Data Factory, Kafka, or comparable orchestration and integration platforms
• Familiarity with enterprise AI platforms such as Azure AI, AWS SageMaker, Google Vertex AI, Databricks Mosaic AI, Snowflake Cortex, NVIDIA NIM, or similar technologies
• Experience using AI tools and coding assistants, such as Claude, Glean, Copilot, and CoCo, with cloud and on premises data platforms
• Experience presenting technical recommendations to customers and executive leadership
• Bachelor's degree in computer science, data engineering, or a related field, or equivalent experience
• Hands on experience with Snowflake and/or Databricks is highly desirable, as most customers we meet use one or both
• Exposure to Microsoft Fabric and similar modern data platforms is also relevant
• Active Databricks and/or Snowflake certification(s) highly preferred
• A minimum of 3 years of relevant technical experience across data engineering and data science, including hands on experience preparing and managing data for data science use cases.

Required skills

• Apache Spark, Cloud Data Platforms AWS, Cloud Data Platforms Azure, Cloud Data Platforms Google Cloud, Customer Advisory, Data Engineering, Data Modeling, Data Science, Databricks, ETL/ELT Pipeline Design, Large Language Models (LLMs), Python, Retrieval-Augmented Generation (RAG), SQL, Snowflake

Experience

• 3+ years