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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Solutions Architect II -- Data Engineer - **Company:** World Wide Technology - **Location:** Maryland Heights, MO, United States (Remote available) - **Experience:** Experienced - **Salary:** $150,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, ARM Architecture, Microsoft Azure, Cloud Computing, Collaborative Software, Customer Data Management, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), IT Management, Python (Programming Language), Metadata, Microsoft Copilot, SQL Databases, Technical Data Management Systems, Google Cloud, Feature Engineering, Data Ingestion, Azure Data Factory, Large Language Models, Snowflake, Apache Spark, Google Vertex AI, Data Strategy, Microsoft Fabric, AI Platforms, Information Technology, Integration Frameworks, Apache Kafka, Data Management, Claude, Nim (Programming Language), Azure AI, Data Pipelines, Databricks - **Published:** October 23, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3466384568&tx=VT6762TYD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role Work Experience: 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. Specialized Knowledge, Skills, and Abilities: * 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. * 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. A PhD is not required. 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. The emphasis is on explaining why data readiness determines whether these solutions work, not on building agents for customers. * 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. Deep cloud infrastructure expertise is not required. * 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. The technologies at the center of this role are new, and the right candidate has learned them by using them and is actively exploring how AI is changing the way data work gets done. * 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. * A passion for helping customers solve complex business problems through trusted data foundations and practical AI. Working conditions (if needed) This is a remote position located within the US, with hours being primarily based on business hours in US time zones. Due to the pace of AI and Data technology adoption, this will be a fast paced position, juggling multiple active engagements. The role demands a high degree of autonomy, requiring the candidate to independently manage tasks and responsibilities. The ability to self motivate and drive initiatives forward in a remote setting is critical. Ideal candidates should be capable of working independently while maintaining close virtual collaboration with the team and stakeholders. Education: Bachelor's degree in computer science, data engineering, or a related field, or equivalent experience. Certifications: Active Databricks and/or Snowflake certification(s) highly preferred., WWT will consider for employment, without regard to disability, a disabled applicant who satisfies the requisite skill, experience, education, and other job-related requirements of the job and is capable of performing the essential requirements of the job with or without reasonable accommodation. World Wide Technology is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity, national origin, age, disability, veteran status, genetic information, or other characteristics protected by law. We are committed to working with and providing reasonable accommodations to individuals with disabilities. If you have a disability and you believe you need a reasonable accommodation in order to search for a job opening or to submit an online application, please call 1-800-432-7008 and ask for Human Resources. ## Description * 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.