Technical Solutions Architect II - Data Engineer

Role Overview

Benefits

• Full-time employees receive health insurance, employee assistance, and wellness programs.
• Benefits include competitive pay, profit sharing, life and disability insurance, and tuition reimbursement.
• Paid time off includes holidays, parental leave, sick leave, and bereavement leave.

Responsibilities

• Lead pre-sales enterprise engagements including workshops, discovery sessions, architecture reviews, and executive briefings.
• Guide customers on data readiness for AI and data foundations that support AI value.
• Advance AI Studio, AI Foundry, and AI Factory service opportunities with account teams.
• Translate complex technical concepts into business and executive stakeholder language.
• Create whitepapers, workshop curriculum, and internal enablement content for AI-ready data.
• Engage AI Proving Ground and partner ecosystems, particularly Databricks and Snowflake, to validate approaches and support the field.

Experience and Technical Requirements

• 10+ years designing, building, and optimizing scalable data platforms with Snowflake, Databricks, and lakehouse architecture.
• Deep hands-on experience with Snowflake and Databricks platform capabilities.
• Strong ETL/ELT, orchestration, workflow automation, batch and streaming processing, and data modeling fundamentals.
• Proficiency in SQL and Python to independently write, debug, and review production-quality code.
• Working fluency in lakehouse and data platform architecture and platform tradeoffs.
• Ability to discuss data quality, security, and trust topics in customer conversations.
• Understanding of how LLM, RAG, and agentic AI workloads consume enterprise data.
• Experience using AI coding assistants and agent tools with cloud data platforms.
• Experience implementing Databricks and Snowflake solutions on Azure, AWS, or Google Cloud.
• Ability to lead discovery, identify technical and organizational gaps, evaluate tradeoffs, and deliver recommendations.
• Experience supporting a non-quota technical advisory services sales motion with account teams.
• Strong communication skills for data engineers, architects, IT leadership, and executive stakeholders.

Preferred Qualifications

• Prior pre-sales, consulting, solutions engineering, or technical advisory experience is preferred.
• Experience with large-scale data platform migrations.
• Experience with BigQuery, Redshift, or Azure Synapse.
• CI/CD, DevOps, and infrastructure-as-code practices for data platforms.
• Metadata management, lineage tooling, and data observability or monitoring experience.
• Familiarity with dbt, Apache Airflow, Azure Data Factory, Kafka, Event Hubs, or comparable tools.
• Familiarity with enterprise AI platforms such as Azure AI, AWS SageMaker, Google Vertex AI, Databricks Mosaic AI, or NVIDIA NIM.
• Active Databricks and/or Snowflake certifications are highly preferred.

Education

• Bachelor's degree in computer science, data engineering, or a related field, or equivalent experience.