03.10.2026 aktualisiert
YL
100 % verfügbar
Enterprise AI & Cloud Solutions Architect | Data Analytics | AWS | Python | 7+ years experience
Tokyo, Japan
Nur Remote
MEngÜber mich
Enterprise AI & Cloud Architecture: Drive AI adoption from use-case discovery and PoC to enterprise rollout using Copilot, Copilot Studio, LLMs, and AI agents. Design scalable data, AI, and MLOps platforms with AWS, Snowflake, Terraform, and CI/CD.
Skills
Künstliche IntelligenzData AnalysisBusiness IntelligenceData ArchitecturePythonMicrosoft Business IntelligenceSolution ArchitectureData ScienceSnowflakeGenerative AIMachine Learning OperationsAws Iot
Data & AI professional with experience across data science, data analytics, business intelligence, machine learning, generative AI, cloud architecture, and enterprise digital transformation.
My expertise includes Python, SQL, data analysis, data visualization, statistical analysis, machine learning, deep learning, predictive modeling, data engineering, ETL/ELT, data modeling, semantic modeling, dashboard development, and business intelligence.
I have extensive experience with Power BI, including data modeling, DAX, Power Query, semantic models, interactive dashboards, KPI reporting, data visualization, and AI-enabled analytics with Power BI Copilot.
My AI and machine learning experience covers traditional ML, deep learning, large language models (LLMs), generative AI, RAG, prompt engineering, AI agents, Microsoft Copilot, Copilot Studio, and enterprise AI solutions.
I also have strong cloud and data platform experience, particularly with AWS, Snowflake, GitHub, CI/CD, cloud architecture, data pipelines, data integration, and scalable cloud-based data and AI solutions.
My project experience spans enterprise AI transformation, business process automation, digital enablement, data analytics and BI platforms, AI adoption, data governance, digital asset management, cloud and data architecture, and SaaS product development. I have also worked on sustainability and CO2 emissions-related SaaS solutions involving data processing, analytics, visualization, and cloud technologies.
I am comfortable working across the full lifecycle of data and AI projects—from understanding business requirements and analyzing data to designing technical architectures, developing analytical and AI solutions, building dashboards and data models, and supporting production deployment and enterprise adoption.
Key areas of expertise include:
Data Science, Data Analytics, Business Intelligence, Power BI, Data Visualization, Data Modeling, Semantic Modeling, Python, SQL, Machine Learning, Deep Learning, Generative AI, LLMs, RAG, AI Agents, Microsoft Copilot, Copilot Studio, AWS, Snowflake, Cloud Architecture, Data Engineering, ETL/ELT, GitHub, CI/CD, SaaS, Enterprise AI Transformation, Digital Transformation, Data Governance, Business Process Automation, Sustainability Analytics, and CO2 Emissions Management.
Erfahrung
Berufserfahrung5 - 10 Jahre
Freelancer seit2022
Sprachen
ChineseGrundkenntnisseEnglishgutJapaneseverhandlungssicher
Projekthistorie
Project: Enterprise AI Transformation & Digital Enablement
Role: Drive enterprise AI transformation by collaborating with business departments to identify high-impact use cases and translate them into scalable solutions using Microsoft Copilot and Copilot Studio. Lead activities from use-case discovery and PoC through solution design, implementation, and enterprise adoption. Also design digital asset governance and development workflows
Achievements: Established GitHub–Snowflake integration and CI/CD workflows for digital asset management. Led the PoC and rollout of Power BI Copilot across multiple business departments. Designed and deployed a Copilot Studio agent integrated with internal knowledge sources such as SharePoint, enabling company-wide enterprise knowledge search. Continue to identify new business use cases and transform repeatable processes into AI-powered agents.
Project: CO2 Emissions Data Analytics SaaS
Role: Processed and transformed CO2 emissions data for integration into anenterprise SaaS application, covering data extraction, cleansing, processing, and application configuration. Supported the end-to-end data workflow using Python, AWS SageMaker, and MongoDB, and prepared technical documentation for users.
Achievements: Delivered processed CO2 emissions data into the SaaS application and supported application-level configuration and enhancements required for data integration. Established a reliable workflow from raw data processing to application ingestion and supported users with operational documentation.
Project: Data Analytics Platform Migration & MLOps
Role: Designed and implemented AWS infrastructure and MLOps environments for enterprise data and AI workloads, covering requirements definition, architecture design, implementation, testing, and knowledge transfer. Built cloud infrastructure using Terraform and other IaC tools with AWS services including SageMaker, S3, ECR, IAM, VPC, Lambda, Glue, and Athena.
Achievements: Delivered end-to-end MLOps environments for 3+ OpCos and established a standardized, reusable infrastructure architecture. Developed IaC patterns to improve consistency across AWS environments, designed infrastructure testing procedures, and prepared technical documentation and knowledge-transfer materials for engineering teams and users