AI / Cloud Data Engineer focused on production-grade AWS platforms, real-time AI systems, analytics engineering, and enterprise-scale data workflows.
AI / Cloud Data Engineer focused on building production-style cloud and AI systems across AWS infrastructure, analytics engineering, orchestration workflows, retrieval-augmented generation (RAG), and real-time intelligent pipelines.
My work combines cloud architecture, data engineering, AI engineering, validation frameworks, observability, and executive analytics platforms designed around production-oriented engineering practices.
I specialize in AWS-native systems involving Athena, Glue, Terraform, Step Functions, Kinesis, Power BI, vector databases, orchestration pipelines, and large language model (LLM) workflows.
Target decision latency for real-time AI and streaming workflows.
Validation pass-rate target across data quality, failure handling, and decision quality checks.
Production-style portfolio projects covering AI, cloud, data engineering, analytics, and orchestration.
Infrastructure-as-Code patterns using Terraform for repeatable AWS deployment workflows.
Grounded retrieval workflows with semantic search, reranking, and validation-oriented AI responses.
CloudWatch-oriented monitoring patterns, execution traces, and operational visibility.
Real-time streaming validation, latency testing, and production-oriented reliability checks.
Validation workflows for data consistency, schema checks, transformation accuracy, and analytics reliability.
Error handling patterns, recovery workflows, defensive pipeline design, and resilient orchestration.
CloudWatch-oriented monitoring, execution visibility, operational metrics, and production-style telemetry.
Terraform-based infrastructure patterns for repeatable, auditable, and cloud-native deployments.
RAG grounding checks, retrieval validation, adversarial testing, and answer quality controls.
Retrieval-augmented generation systems, semantic search pipelines, vector retrieval, grounding workflows, and AI explanation layers.
AWS-based analytics platforms using Athena, Glue, S3, Terraform, orchestration, validation, and production-style data workflows.
CFO-oriented dashboards, FinOps analytics, Power BI reporting, cost variance analysis, and business decision intelligence.
Production-style real-time AI financial intelligence platform using streaming pipelines, multi-agent orchestration, RAG systems, Terraform, validation pipelines, and AWS cloud architecture.
View ProjectCloud-native CFO FinOps analytics platform combining AWS Athena, Power BI, retrieval-augmented generation, observability, orchestration, and analytics engineering workflows.
View ProjectModern analytics engineering project using dbt, Docker, dimensional modeling, ELT workflows, SQL transformations, and analytics marts.
View ProjectWorkflow orchestration project using YAML pipelines, ETL automation, cloud ingestion workflows, PostgreSQL, and modern data engineering practices.
View ProjectSemantic retrieval and RAG experimentation project focused on embeddings, document retrieval, vector search, and AI pipeline prototyping.
View ProjectVector search experimentation project focused on embeddings, similarity retrieval, vector databases, and AI-powered search workflows.
View ProjectCloud architecture, AWS services, reliability, networking, security, and scalable design.
Power BI modeling, dashboarding, analytics reporting, and executive business intelligence.
Cloud cost management, optimization, forecasting, showback, and financial governance.
Data analysis foundations, SQL, spreadsheets, visualization, and analytics workflows.
Python data analysis, pandas, data cleaning, exploration, and analytical workflows.
RAG, LangChain, prompt engineering, LLM systems, AI agents, and evaluation workflows.