Oneill Taylor Senior Data + AI Engineer
Summary

Principal Data & AI Engineer with 10+ years of experience designing multi-cloud data architectures, building and deploying applied AI/ML solutions, and leading enterprise-scale AI transformation initiatives across Energy, Utilities, and Automotive industries. Proven expertise integrating Salesforce Data Cloud with Databricks, Snowflake, and hyperscaler platforms to enable scalable AI workloads and real-time analytics.

Skills
Languages: Python, JavaScript (ES6+), TypeScript, Java, SQL, HTML5, CSS3, Bash, PowerShell
Frameworks: Django, Flask, FastAPI, React.js, Redux, Next.js, Node.js, Express, GraphQL, RESTful APIs, JSON, WebSockets
AI/ML: TensorFlow, Keras, PyTorch, Scikit-learn, OpenCV, spaCy, NLTK, Hugging Face Transformers, OpenAI / Azure OpenAI APIs, LangChain, RAG (Retrieval-Augmented Generation), AutoGen, Voiceflow, Microsoft Copilot, NLP, LLM Fine-tuning, Generative AI, Prompt Engineering, MLflow, Vertex AI, Azure Machine Learning, SageMaker
Data & ETL: Apache Airflow, Apache Spark, Hadoop, Kafka, RabbitMQ, DBT, ETL Pipelines, Data Warehousing, Data Lakehouse Architectures, Delta Sharing, Databricks, Snowflake, AWS Glue, Azure Synapse, GCP Dataflow, ELT Automation
Database & Storage: PostgreSQL, MySQL, MongoDB, DynamoDB, AstraDB, Firebase, Redis, Cassandra, RDS, BigQuery, S3, Data Cloud, Cosmos DB
Data Analysis & Machine Learning: Pandas, NumPy, SciPy, Matplotlib, Seaborn, Plotly, D3.js, Tableau, Power BI, Regression & Classification Modeling, Feature Engineering, Clustering, Decision Trees, Random Forest, Neural Networks, Model Evaluation, A/B Testing
Cloud & Devops: AWS, GCP, Azure, Docker, Kubernetes (EKS), Terraform, Ansible, CI/CD, Jenkins, GTM, Prometheus, Grafana
Others: Agile/Scrum, Project Management, Debugging, OOP, Jinja, Linux, Git, Strategic Thinking, Analytical Skills, Communication & Documentation, Time Management, Team Collaboration, Creative Problem-Solving, Detail-Oriented, Multitasking, Regression, Clustering, Decision Trees, Random Forest, Neural Networks, Classification, Dimensionality Reduction
Professional Experience

Principal Data + AI Engineer

Salesforce
2021 – 2025
  • Architect end-to-end multi-cloud data and AI platforms integrating Salesforce Data Cloud, Databricks, Snowflake, and AWS/GCP/Azure services to support large-scale enterprise AI deployments across Energy, Utilities, and Automotive industries.
  • Designed and deployed LLM-powered prototypes and proof-of-concepts demonstrating real-time analytics, predictive modeling, and generative AI capabilities using Salesforce Einstein and external ML frameworks.
  • Established a Global AI Enablement Program, creating hands-on training modules, internal datasets, and reusable ML templates to scale the organization’s AI/ML maturity globally.
  • Partnered with product and research teams to influence AI roadmap direction, providing architectural patterns and feedback that improved inference speed and model integration with customer environments by 30%.
  • Served as technical lead and interim manager for the Global Industries AI Engineering team—defining priorities, overseeing model deployment standards, and ensuring platform reliability across multi-region accounts.
  • Acted as a strategic data and AI advisor to enterprise clients, guiding them through architecture modernization, vector database adoption, and zero-copy data sharing patterns for ML workloads.
  • Led recruitment and mentorship for new data and AI engineers, establishing onboarding frameworks and internal certifications to accelerate hands-on technical competency in ML and data engineering.
  • Designed and implemented enterprise-grade AI architectures integrating Salesforce Data Cloud with Databricks, Snowflake, and AWS Redshift to enable real-time data activation and model inference directly within Salesforce.
  • Engineered custom proof-of-concepts for Agentforce AI, applying NLP and unstructured data processing to demonstrate intelligent agent use cases, resulting in a 110% average quarterly quota attainment.
  • Developed zero-copy data pipelines leveraging Delta Sharing and live query patterns, reducing data duplication and improving inference latency for large clients by 25%.
  • Collaborated with Data Science teams to deploy predictive and generative AI models into production environments via Salesforce APIs and MLOps frameworks.
  • Created AI consumption cost simulators to model data storage, inference, and training expenses—driving informed cloud architecture decisions and cost optimization for clients.
  • Delivered multiple technical sessions at Databricks Data + AI Summit, Dreamforce, and Tableau Conference, demonstrating advanced MLOps and multi-cloud data integration best practices.
  • Partnered cross-functionally with Product, Core, and Cloud teams to standardize AI reference architectures and ensure operational reliability across distributed data systems.
  • Led architecture and development of data-driven CRM + AI solutions for global manufacturing clients, connecting enterprise data pipelines to AI-enabled Salesforce applications.
  • Built custom ETL and data modeling solutions for $9M+ average opportunity value (AOV) accounts, enabling predictive analytics and operational intelligence dashboards.
  • Designed data integration blueprints connecting Salesforce with Azure Synapse, Snowflake, and on-prem ERP systems using API-led and event-driven architectures.
  • Developed and automated custom AI insights pipelines, transforming structured and unstructured data into model-ready datasets for downstream machine learning applications.
  • Spearheaded cross-functional workshops translating business KPIs into data and ML use cases—driving client adoption of predictive maintenance and sales forecasting models.
  • Awarded MVP Q3 2022 for innovation and volunteer leadership in AI/CRM enablement initiatives across the manufacturing vertical.
  • Sales and Contact Center Manager

    McNICHOLS CO
    2015 – 2020
  • Served as business stakeholder and data lead for a major CRM migration, designing data models and automations that reduced swivel-chairing by 20% and improved workflow efficiency across 15 sales agents.
  • Drove implementation of an AI-powered chatbot solution integrated with CRM data to deflect 25% of inbound calls while maintaining service quality.
  • Built and maintained sales analytics dashboards and forecasting models to improve resource allocation, leading to a 5% improvement in first-call resolution and SLA compliance.
  • Partnered with the Center of Excellence to modernize data and telephony systems, integrating AS400, CRM, and automation tools to enable centralized reporting and analytics.
  • Engineered ETL processes for merging regional sales data into a unified data mart, improving executive visibility and enabling predictive sales forecasting.
  • Analyzed multi-year sales data using SQL and Python to identify key growth patterns that contributed to a 45% YoY revenue increase across the West Region.
  • Developed governance processes for sales enablement and training data collection, ensuring consistent measurement of performance and learning outcomes.
  • Managed a 15-person sales and service team, coaching them to adopt data-driven decision-making through visualization and self-service analytics dashboards.
  • Leveraged data analytics to identify upsell and cross-sell opportunities, increasing average order value by 20% YoY.
  • Built Excel and SQL-based reporting automations that streamlined sales tracking and performance analytics, reducing manual reporting by 40%.
  • Collaborated with IT to implement new CRM and analytics platforms, serving as a super user and data validation lead.
  • Supported digital marketing campaigns by creating data-driven customer segmentation models that improved lead targeting efficiency.
  • Mentored new team members on data tools, pipeline processes, and CRM adoption best practices.
  • Predictive Sales Forecasting – Built regression-based forecasting model for manufacturing client using Snowflake + Python, improving forecast accuracy by 18%.
  • Data Cloud AI Integration – Designed prototype linking Salesforce Data Cloud with Databricks for LLM-powered insights using customer data.
  • Data Cost Optimization Framework – Automated Snowflake usage analysis to optimize storage and compute, cutting client spend by 22%.
  • Senior Data / AI solutions consultant

    Neba
    2015 – 2020
  • Led data modernization and AI readiness projects for SMB and mid-market clients, migrating legacy systems to modern cloud architectures using Azure, Snowflake, and BigQuery.
  • Designed and implemented end-to-end data pipelines that replaced Excel-based analytics with automated ETL workflows, cutting data preparation time by 70% and enabling advanced BI reporting.
  • Architected customer segmentation and campaign optimization models leveraging SQL, Python, and BigQuery ML, resulting in a 30% increase in marketing ROI for multiple clients.
  • Collaborated with cross-functional teams to automate business processes through workflow orchestration and API integrations, reducing manual work by 15–20%.
  • Developed and maintained eCommerce analytics and recommendation systems for Shopify and WordPress stores, integrating clickstream data for product optimization insights.
  • Served as a Salesforce implementation consultant, deploying multi-cloud solutions and integrating CRM data with Snowflake for unified analytics.
  • Managed a small team of developers to deliver data platform builds, ETL frameworks, and ML prototypes, ensuring scalability and documentation aligned with best engineering practices.
  • Designed and presented data architecture blueprints and ROI-driven AI strategies to executive stakeholders, helping clients define KPIs and track measurable digital transformation outcomes.
  • Education

    Bachelor's Degree in Business Information Systems & Data Science

    California State University, Fullerton

    Master's Degree in Data Analytics and Data Engineering

    Western Governors University
    Certificates
    Google Cloud Digital Leader

    Google

    Salesforce Certified Data Cloud Consultant

    Salesforce

    Microsoft Certified: Azure Data Fundamentals

    Microsoft

    Salesforce Certified AI Associate

    Salesforce

    Big Data and Artificial Intelligence Certification

    Ashland University

    Data Analytics Professional Certificate

    Western Governors University