TAYLOR AMAREL

TAmarel.Tech@gmail.com | linkedin.com/in/tayloramareltech

PROFESSIONAL SUMMARY

Distinguished Data Technology Leader with over a decade of experience architecting enterprise-scale data solutions and driving digital transformation initiatives. Demonstrated expertise in implementing modern data mesh architectures, real-time analytics platforms, and AI/ML solutions that deliver measurable business value. Proven track record of building and leading high-performing teams while establishing data-driven cultures across organizations. Specialized in designing scalable data infrastructure that combines cloud-native technologies, advanced analytics, and machine learning to solve complex business challenges.

PROFESSIONAL EXPERIENCE

Data Analytics Lead

ADUSA (Formerly Retail Business Services) | May 2022 – July 2024

• Spearheaded the implementation of a modern data mesh architecture using Databricks Delta Lake, enabling self-service analytics and reducing time-to-insight by 40%
• Architected and deployed real-time data pipelines using Apache Kafka and Azure Event Hubs, processing over 1M events per second for inventory optimization
• Developed comprehensive MLOps framework using Azure ML and GitHub Actions, reducing model deployment time from weeks to hours
• Implemented advanced data quality monitoring using Great Expectations and dbt, achieving 99.9% data accuracy across critical datasets
• Led the adoption of Power BI Premium features including automated machine learning and real-time streaming, serving 500+ daily active users
• Established data governance frameworks using Azure Purview and Collibra, ensuring CCPA and GDPR compliance
• Integrated computer vision models for shelf analytics using TensorFlow and Azure Computer Vision, improving stock accuracy by 35%

Technology Solutions Director

Migrasia | July 2017 – January 2022

• Designed and implemented data lake solution using Databricks and Delta Lake, incorporating bronze/silver/gold medallion architecture
• Developed automated ETL workflows using Apache Airflow and dbt for robust data transformation and testing
• Implemented real-time analytics using Kafka Streams and ksqlDB, processing billions of events daily
• Created custom NLP models using BERT and GPT for automated document processing and sentiment analysis
• Utilized container orchestration with Kubernetes and Azure AKS for scalable microservices deployment
• Implemented CI/CD pipelines using GitHub Actions and Azure DevOps for automated testing and deployment
• Developed custom recommendation engines using collaborative filtering and deep learning approaches

Technology Consultant & Entrepreneur in Residence

Amarel Solutions | October 2011 – July 2017

• Architected cloud-native solutions using AWS Lambda and Azure Functions for serverless computing
• Implemented data warehousing solutions using Snowflake and BigQuery for analytical workloads
• Developed real-time dashboards using Grafana and Elasticsearch for operational monitoring
• Created automated testing frameworks using Pytest and JUnit for quality assurance
• Utilized infrastructure as code practices with Terraform and CloudFormation

TECHNICAL EXPERTISE

Data Engineering & Architecture

• Data Platforms: Databricks, Snowflake, Azure Synapse Analytics, Google BigQuery
• Stream Processing: Apache Kafka, Azure Event Hubs, Amazon Kinesis, RabbitMQ
• ETL/ELT Tools: Apache Airflow, dbt, Azure Data Factory, Informatica
• Data Quality: Great Expectations, dbt Tests, Apache Griffin
• Data Governance: Azure Purview, Collibra, Apache Atlas
• Version Control: Git, GitHub, Azure DevOps, GitLab

Cloud & Infrastructure

• Platforms: Azure (Solutions Architect), AWS (Advanced), GCP (Professional)
• Containers: Docker, Kubernetes, Azure AKS, Amazon EKS
• IaC: Terraform, CloudFormation, Pulumi
• Security: Azure Key Vault, AWS KMS, OAuth 2.0, RBAC

Analytics & Visualization

• BI Tools: Power BI Premium, Looker, Tableau, Qlik
• Monitoring: Grafana, Kibana, Azure Monitor
• SQL Engines: Apache Spark SQL, Presto, Trino
• NoSQL: MongoDB, Cassandra, Redis, Neo4j

Programming & Development

• Languages: Python (Advanced), SQL, R, JavaScript, Java
• Frameworks: FastAPI, Flask, Django, Spring Boot
• ML Libraries: TensorFlow, PyTorch, scikit-learn, XGBoost
• Big Data: Apache Spark, Hadoop, Hive, Delta Lake

AI/ML & Advanced Analytics

• Deep Learning: CNN, RNN, LSTM, Transformers
• MLOps: Azure ML, MLflow, Kubeflow, TensorFlow Extended
• NLP: BERT, GPT, spaCy, NLTK
• Computer Vision: OpenCV, TensorFlow Vision, Azure Computer Vision

EDUCATION

Master of Science in Data Analytics and Machine Learning Western Governors University | 2023

• Research Focus: Explainable AI in Enterprise Systems
• Thesis: “Implementing Interpretable Machine Learning Models for Business Decision Systems”

Bachelor of Science in IT Management Western Governors University | 2022

• Concentration in Data Systems and Cloud Architecture
• Capstone: “Design and Implementation of Cloud-Native Data Platforms”

CERTIFICATIONS

• Azure Solutions Architect Expert (2024)
• AWS Advanced Data Analytics Specialty (2024)
• Google Cloud Professional Data Engineer (2023)
• Databricks Certified Developer (2023)
• Power BI Expert Certification (2023)

METHODOLOGIES & BEST PRACTICES

• Data Mesh Architecture
• Domain-Driven Design
• GitOps & DataOps
• Agile & Scrum
• Site Reliability Engineering
• Zero Trust Security
• Event-Driven Architecture
• Continuous Integration/Deployment
• Test-Driven Development
• Infrastructure as Code