Data Engineer with specialization in Data Warehouse and ETL. Over 20 years of hands-on experience designing cloud/on-premise DWH architectures, data models, and ETL/ELT pipelines — from greenfield builds to large-scale legacy migrations. If you need to build a BI/DWH/Database solution from scratch till production or need support in any part of the project - don't hesitate to contact me. What I bring to the table: -> Snowflake + DBT: Built event-driven data architecture at Fundbox ($5B+ fintech), supporting real-time credit decisions across loan origination, payment processing, and risk assessment. -> AWS Cloud: Led enterprise migration of 50TB+ databases to AWS for IBM Acoustic at ClearScale. Designed pipelines handling 2B+ daily records with 99.99% accuracy. -> Data Architecture: Star Schema, Data Vault, dimensional modeling — not just theory but production implementations across fintech, healthcare, pharma, telecom, and retail. -> AI-Augmented Development: Built MCP Server integrations connecting Redshift, MySQL, Git, and Jira with LLM-powered workflows. Created dashboards-as-code, using AI generation. Currently building DWH and BI solutions for a healthcare Florida local company, using AWS Redshift, QuickSight, and Python. Tech: Snowflake, DBT, AWS Redshift, Python, SQL, Terraform, Montecarlo, QuickSight, Tableau Modeling: Star Schema, Data Vault, Dimensional Modeling Legacy: Informatica, DataStage, Talend, Oracle, Netezza (for migration projects) Status: U.S. Permanent Resident. No sponsorship required. Open to: Senior Data Engineer, Data Engineer, Analytics Engineer roles — remote or Tampa FL, hybrid. I can help you in these areas - BI Solution Architecture Development, Data Warehouse project - Data Model Design (Logical, Physical, Star/Snowflake, Multidimensional, Data Vault) - Database design (Snowflake, Redshift, Oracle, MS SQL, Netezza, Vertica, PostgreSQL) - Data Management (Migration, Integration, Replication and any data processing) - ETL development (DBT, Talend, DataStage, IICS, PowerCenter, SSIS, Talend, ODI, AWS) - Data Quality and Data Cleansing - Create complex DB Server-side logic (Procedures/Functions, UDF/UDA) - Performance tuning (SQL queries, PL/SQL, T-SQL, NZSQL)

I'm a versatile freelance Data Engineer with a strong command of various tools and technologies. Proficient in PySpark, Python, Azure Data Factory, Google BigQuery, SQL, and more, I'm your go-to expert for designing and implementing efficient data solutions. With a focus on optimizing data processes, I bring a wealth of experience to help you derive valuable insights from your data. If you're in need of a skilled Data Engineer to tackle your data challenges, let's connect and discuss your project. Delivered $50K+ in data engineering solutions across 15 projects | Specializing in scalable ETL pipelines, real-time data processing, and cloud data architecture (Azure, GCP) | Built systems processing 10M+ records with 40% improved performance | Expert in PySpark, Python, BigQuery, and Azure Data Factory SQL Python API Integration Data Extraction Data Transformation Amazon EC2 Data Engineering Data Visualization PySpark Apache Spark AWS Glue Apache Airflow Data Warehousing & ETL Software Jupyter Notebook Amazon Web Services LLM Prompt Prompt Engineering Generative AI Model Tuning Generative AI Prompt Engineering

Hello I'm Jay, I’ve worked on building end-to-end data systems for more than 11 years, including: Data pipelines (ETL/ELT) from multiple sources (APIs, databases, files) Batch processing(Spark), Streaming processing(Flink) Modern data warehouses (BigQuery, Snowflake, Redshift) Data transformation and modeling using dbt Interactive dashboards (Power BI / Tableau) Web scraping and structured data extraction API integration and workflow automation AI-powered analytics using OpenAI / LLMs 💡 Why choose me: Strong engineering + analytics background (not just visualization) Experience with modern data stack (ELT, dbt, cloud warehouses) Focus on business value, not just technical delivery Clear communication and fast iteration(English, Cantonese) ⏰ Availability (Global Time Zones) (🇨🇳 Beijing) UTC+8, available 08:00 AM – 02:00 AM (🇬🇧 London) UTC+0, available 12:00 AM – 06:00 PM (🇺🇸 New York) UTC-5, available 07:00 PM – 01:00 PM

I have several years of experience, using multiple programming languages and frameworks, in both academia and industry, in statistical modeling, probabilistic programming, classical machine learning and application of deep learning in several domains. The last several years I have been primarily ad cloud and data architect and data engineer and AI engineer. I have extensive experience in data modeling, pipeline development, data compliance, and worked with several database technologies (relational, NoSQL, graph, Hadoop and Spark), as well as CI/CD, API development, and architecting and development with multi-cloud computing platforms (Microsoft Azure, AWS, and GCP). I have deep experience in Databricks, and am a certified data engineer professional. 

I have worked in various fields such as, statistical genetics, behavior genetics, computational social science, app development, FinTech and healthcare data. The last 3 years I have run a consultancy while also building two profitable startups as data architect, data engineer while also being responsible for AI engineering and machine learning. Current Certifications: Databricks: Data Engineer Professional Azure: Developer, Data Scientist, Data Engineer, AI Engineer AWS: Data Engineer GCP: Data Engineer I have an extensive background in Python, R, JavaScript, SQL (T-SQL, PostgreSQL, SparkSQL, Databricks SQL, CQL, HiveQL, Cypher, KQL), with most data science libraries such as Pandas, NumPy, Scikit-learn, SciPy, SymPy, Rapids, PySpark, TensorFlow and TensorFlow Probability, Keras, PyTorch. I have extensive experience with standard data engineering tools: Snowflake, Databricks, Spark, PostgeSQL , dbt , Neo4j, Hadoop, Airflow, Beam, Iceberg, Hive, Kafka

, AirFlow, Flink, SuperBase, Hadoop, Dagster, Prefect, dot. As well as deep experience with several AI frameworks and automation tools: DSPy, LlamaIndex, BAML. LangChain, Hugging Face, AutoGen, LangGraph, a2a, MCP the AI frameworks of all 3 major cloud providers, n8n, Make, PipeDream, Flowise, Zapier, 5 Tran, and AirByte. 
I have extensive experience with multiple cloud providers, especially with the following skills and cloud products:
 General Cloud Development: Databricks in any cloud Azure: Storage, Networking, Functions, VMs, App Service, Synapse, Data Factory, DevOps, Kubernetes Service, API Management, Service Bus, Event Hubs, Event Grid, PubSub, Notification HubsRelay, IoT Hub, Power Apps, Power Automate, Azure Machine Learning, Synapse Analytics, Data Lake Storage, SQL Server, Cosmos DB, Data Flow, Stream Analytics, HDInsight, Redis, Cognitive Services, Text Analytics Service, LUIS, Custom Vision, Bot Service, Cognitive Search, and the general Power Platform AWS: S3, EBS, EC2, Lambda, Networking, RDS, Redshift, Arora, Athena, DynamoDB, DocumentDB, Lake Formation, Glue, Redis, SageMaker, Bedrock, Kinesis, QuickSight Elasstic Beanstalk, Elastic Kubernetes Service, Databricks, Pipeline, EMR, CloudWatch GCP: Storage, Networking, Cloud Functions, VMs, App Engine, Kubernetes Engine, API Gateway, BigQuery, BigTable, DataProc, Composer, DataFlow, Data Fusion, Data Studio, Cloud SQL, CloudSpanner, Cloud Memorystore, Pub/Sub

Hi. I am a solution architect, data engineer and analyst with deep experience in designing and building modern data platforms that power analytics, automation and AI. My expertise spans large-scale data processing, data modeling, integration and orchestration across complex enterprise environments. I specialize in architecting and engineering robust, high-performance data solutions that deliver reliability, scalability and business impact. I work extensively with modern data architectures including lakehouse, data warehouse and Data Vault 2.0, implementing data pipelines that ensure structured, governed and high-quality data delivery. My experience includes building metadata-driven frameworks, batch and streaming ingestion patterns and orchestrated ETL/ELT processes that support analytics and machine learning use cases. Technically, I am highly proficient in Python for data transformation, validation and automation using libraries such as pandas, pyarrow, pyspark, dbt, great-expectations, mlflow, sklearn, pytorch and the AzureML Python SDK. I also leverage Spark for distributed processing and scalable data engineering workloads. In the analytics and visualization space, I bring strong expertise with Power BI and Microsoft Fabric, enabling complete data delivery from ingestion to actionable insights. I design interactive dashboards and analytical reports that help business users explore their data with clarity and confidence. My Power BI experience covers the full lifecycle from wireframing in Figma or NudgeBI to data preparation with Power Query (M language), semantic modeling with DAX and building engaging visuals using both native and custom tools such as Deneb (Vega-Lite) and SVG. My Fabric experience spans Lakehouse, Data Warehouse, Pipelines, Notebooks and OneLake integration, ensuring seamless connectivity between the data engineering and analytics layers. One of my major projects was with a national telecommunications company, where I contributed to the establishment of the platform landing zone and led key data platform initiatives including the Network Data Platform, the Broadband Analytics data platform for the consumer line of business and the Customer Insights 360 platform for the B2B line of business. One of the key challenges in this engagement was ensuring enterprise security and compliance with the organization’s specific security baseline. I also managed multiple stakeholders and worked closely with the Data Governance Council to ensure processes, standards and governance practices were properly followed throughout the project lifecycle. Beyond technical skills, I have a strong foundation in Enterprise IT project delivery having worked with large organizations as part of a Microsoft CSP partner. I am adept at breaking down complex technical initiatives into manageable work packages and leading multi-disciplinary teams to deliver successful outcomes. My experience across analytics, DevOps and cloud architecture allows me to bridge strategy and execution effectively. Microsoft Azure Data & AI Solution Area certification highlights: ▪ Microsoft Certified Azure Solutions Architect Expert ▪ Microsoft Certified DevOps Engineer Expert ▪ Microsoft Certified Cybersecurity Architect Expert ▪ Microsoft Certified Azure Data Engineer Associate ▪ Microsoft Certified Azure Data Scientist Associate ▪ Microsoft Certified Azure AI Engineer Associate ▪ Microsoft Certified Fabric Analytics Engineer Associate ▪ Microsoft Certified Fabric Data Engineer Associate ▪ Microsoft Certified Power BI Data Analyst Associate ▪ Microsoft Certified Azure Cosmos DB Developer Specialty

I’m a Senior Data Engineer and Python Developer with 9+ years of experience designing and building robust, scalable data pipelines and backend services that transform raw data into actionable insights. My work helps clients streamline their data workflows, enable data-driven decision-making, and optimize business processes. I specialize in eCommerce and advertising data, including integrations with Amazon Ads API (Sponsored Products & Sponsored Brands) for campaign performance tracking, attribution modeling, and bid optimization. I also handle multi-source data ingestion from APIs, CSV/JSON/XML files, web scraping, and OCR pipelines. My services include: ✅ Designing and developing ETL/ELT pipelines for large-scale, multi-source data ✅ Building custom Python scripts for data processing, automation, and analytics ✅ Creating backend services and APIs using Flask for data-driven applications ✅ Rapid prototyping and Streamlit apps for internal tools and dashboards ✅ Deploying containerized applications with Docker for consistent environments ✅ Orchestrating workflows with Apache Airflow/Prefect ✅ Leveraging AWS services including S3, Lambda, Kinesis, Redshift, and RDS ✅ Integrating Amazon Ads API and building marketing analytics pipelines With me, you will: ★ Gain confidence in your data solutions ★ Move past roadblocks and start implementing scalable systems ★ Turn raw data into analytics-ready, actionable insights ★ Leverage my expertise in Python, ETL, AWS, and AdTech to grow your business My tech stack: Python, SQL, Flask, PostgreSQL, MySQL, NoSQL, Apache Airflow, Prefect, Docker, AWS, Amazon Ads API, Streamlit, Plotly, HuggingFace, OCR, Web Scraping Let’s collaborate to turn your data into a strategic advantage. I guide you from concept to production, ensuring high-quality, reliable solutions every step of the way.

Hi 👋 I’m a Data Engineer at GroupBWT - a 100+ person data engineering company and official Snowflake & Databricks partner, delivering enterprise-scale data solutions since 2008. For over 15 years, I’ve been transforming fragmented and inconsistent data into structured, analytics-ready ecosystems by designing and building scalable ETL/ELT pipelines and cloud data platforms using Snowflake, Databricks, and BigQuery, integrated with BI tools like Power BI and Tableau. The outcome is reliable, automated analytics infrastructure that reduces manual reporting effort, speeds up decision-making, and delivers significant operational savings - typically in the range of $20K-$80K annually through improved efficiency and automation. 🌍 What We Deliver As a Data Engineer, I focus on measurable business impact: ✅ 60M+ records/month processed through resilient pipelines with retries, monitoring, and SLA tracking ✅ Up to 70% faster reporting cycles - dashboards refreshing in near real time instead of hours ✅ 15-30% 🔁 My Workflow as a Data Engineer 📦 Data Ingestion & Integration A skilled Data Engineer builds ingestion systems that handle API, CRM, SaaS, and IoT data at scale. ✔ OAuth2, JWT, API key auth, pagination, rate limits ✔ Batch + streaming ingestion with Airflow, Prefect, Kafka ✔ Dynamic configs and feature flags for multi-source onboarding ✔ SLA monitoring to track data freshness and pipeline uptime Example: as a Data Engineer, I built a platform syncing 400K+ SKUs/day into Snowflake with <1% data loss 🧹 Data Transformation & Modeling Every Data Engineer knows data quality drives analytics. ✔ Schema mapping, deduplication, anomaly detection ✔ dbt tests for null ratios, PK/FK consistency ✔ ML/NLP enrichment for classification and tagging Example: as a Data Engineer, I merged ERP + CRM + distributor data into Snowflake with <1% mismatch and documented lineage 📤 Data Loading & Warehousing A professional Data Engineer delivers fault-tolerant pipelines. ✔ Partitioning, clustering, cost optimization ✔ Logging, retries, rollback protection Example: Snowflake ELT optimizing 1B+ rows with dbt, reducing query cost by 40% and improving dashboard load times 3×. 📊 Analytics & BI Enablement Being a Data Engineer means ensuring data is analytics-ready. ✔ <5–10 min latency from source to dashboard ✔ Consistent KPIs with semantic metric layer ✔ Governance and security practices Example: pipelines by a Data Engineer processing 50M+ rows into BigQuery, cutting ad-hoc requests by 60% ⚙️ Tech Stack As a Data Engineer, my toolbox includes: Languages: Python (pandas, numpy, sqlalchemy, PySpark), SQL, JavaScript Warehouses: Snowflake, Databricks Delta Lake, BigQuery, PostgreSQL Orchestration: Airflow, Prefect, dbt, Luigi, Kafka, Spark Clouds: AWS (S3, Glue, Lambda), GCP (BigQuery, Dataflow), Azure Data Factory BI: Power BI, Tableau 🧩 Sample Projects Each project highlights my Data Engineer experience: ✅ Retail Data Platform: 50M+ records/month → Snowflake, +35% inventory accuracy, –65% manual work ✅ Government ETL: as a Data Engineer, I automated 15K+ PDFs/day with NLP → Snowflake + compliance dashboards ✅ Fintech Analytics Hub: Databricks pipelines by a Data Engineer integrating 70+ APIs, –50% compliance prep time ✅ eCommerce Migration: MSSQL + Excel → BigQuery, redesigned data model by a Data Engineer, saving $35K/year ✅ IoT Pipeline: streaming 1M+ events/hour built by a Data Engineer, downtime –20% ✅ HealthTech Integration: HIPAA-compliant ETL across 5 EHRs, dashboards for care teams ✅ Marketing Data Warehouse: unified ad platforms into Snowflake, ROAS dashboards, –15% spend anomalies 🤝 Why Clients Work With a Data Engineer Like Me ✅ Production-Ready Data Pipelines A seasoned Data Engineer delivers reliable data ecosystems with monitoring, retries, lineage tracking, and automated CI/CD deployments. 🔹 95% fewer pipeline failures and 70% reduction in manual interventions 🔹 ROI: $60K-$120K/year saved through automation and error prevention 🔹 Fully auditable datasets supporting GDPR/SOX compliance and investor reporting ✅ Scalable Architecture Solutions from a Data Engineer scale from 50K to 12M+ daily events with no downtime or performance issues. 🔹 100M+ records/month processed from 80+ APIs and data feeds 🔹 Pipelines refresh in under 5 minutes, keeping dashboards current and decision-ready ✅ Data-Driven Decision Making An expert Data Engineer ensures data becomes actionable intelligence, not just storage. 🔹 85% faster reporting cycles, providing leadership with same-day insights 🔹 Finance, sales, and ops align around a single trusted data model 🔹 Power BI/Tableau dashboards improve forecasting accuracy by 30-45% and reveal anomalies before they impact revenue 🚀 Ready to work with a Data Engineer who builds future-proof data platforms? ➡️Invite me to your job and we’ll design a scalable Python ETL solution - with monitoring, tested transformations, and real-time analytics. Last updated May 8, 2025

With years of hands-on experience in AWS, ETL engineering, AI, LLM integrations, business automation and business integration, I help teams fix broken pipelines, build end-to-end cloud architectures, and deploy intelligent automation that saves time and reduces operational friction. I build scalable AWS data platforms and AI-powered automation systems that transform raw, messy data into fast, reliable, and intelligent pipelines ready for analytics and production workloads. I build reliable business automation using APIs, Zapier, n8n, and custom middleware. I deliver End-to-end business automation, API-first integrations, and production-grade AI systems across AWS, Zapier, n8n, and custom Node/PHP service 🔹 What I Do Best (and Deliver Quickly) 1️⃣ Scalable AWS Data Engineering High-volume ETL/ELT pipelines (Glue, Lambda, Step Functions, EMR, Athena) Redshift & Lakehouse architecture Streaming ingestion (Kinesis, MSK) Optimized S3 → Warehouse workflows dbt transformations & data modeling 2️⃣ AI & Machine Learning Systems Predictive analytics, forecasting, anomaly detection SageMaker pipelines & model deployment PyTorch & Python ML systems Evaluation, monitoring, and production optimization 3️⃣ LLM / RAG / AI Automation Retrieval-Augmented Generation (LangChain, LlamaIndex) Document intelligence & PDF processing LLM agents using OpenAI, Anthropic, Gemini Model Context Protocol (MCP) integrations Chatbots with citations, vector search, and advanced retrieval 4️⃣ Infrastructure & DevOps Terraform, CloudFormation, CI/CD (GitHub Actions) Highly available containerized workloads (ECS, EKS) CloudWatch dashboards, Prometheus monitoring End-to-end system hardening & cost optimization 5️⃣ Business Automation & System Integration End-to-end business automation and business integration solutions Workflow automation using Zapier and n8n for rapid orchestration Custom Node.js and PHP-based middleware for complex or non-standard integrations API-first system design (SP-API, internal tools, SaaS platforms) Reliable, observable automation pipelines (not brittle scripts) 🔹 My Stack Programming & Data: Python | SQL | PySpark | Node.js | PHP | Java | Scala | Bash | REST APIs | JSON | Data Structures | Algorithmic Problem Solving Cloud & Data Engineering: AWS (Glue | Lambda | S3 | Redshift | Athena | Step Functions | EMR | EventBridge | CloudWatch) | Databricks | dbt | Data Lakes | Lakehouse Architecture | ETL/ELT Pipelines | Data Warehousing | Serverless Architecture | Cloud Security | Cost Optimization | GCP Big Data & Analytics: Apache Spark | Distributed Data Processing | Data Modeling | Analytics Engineering | Business Intelligence | Batch Processing | Streaming Data Pipelines | Data Quality Frameworks | KPI & Metrics Design | SQL Optimization | Query Performance Tuning | Reporting Pipelines AI & Machine Learning: Machine Learning | NLP | Predictive Analytics | LLMs | RAG Systems | OpenAI | Anthropic | Gemini | LangChain | Document Intelligence | Supervised Learning | Unsupervised Learning | Feature Engineering | Model Evaluation | Model Deployment | AI Automation Automation & Integration: Zapier | n8n | Business Process Automation | API Integrations | Event-Driven Workflows | Workflow Orchestration | SaaS Integrations | CRM Automation | Data Sync Pipelines | Webhooks | Low-Code / No-Code Automation | Operational Automation DevOps & Infrastructure: Terraform | Docker | CI/CD | GitHub | GitHub Actions | Cloud Automation | Monitoring I build systems that are scalable, resilient, cost-efficient, and automation-first, designed to integrate seamlessly into real business operations and grow with demand. Let’s Build Something That Scales Whether you need a high-throughput ETL pipeline, a cloud-native AI system, or a fault-tolerant LLM/RAG application, I can help you deliver it quickly and cleanly. Send me a message, I’d love to understand your system and see how I can help.

I help e-commerce and retail businesses turn Shopify and Ads data into reliable analytics they can trust, not just dashboards. Most growing stores struggle with disconnected data, conflicting revenue numbers, and Excel-based reporting. I build clean, scalable analytics foundations so teams can trust their numbers and make better decisions. What I help with Shopify, GA4, and Ads data in BigQuery Analytics-ready data models using dbt Reliable revenue, customer, and marketing metrics Self-serve dashboards that replace spreadsheets Tools: Python, SQL, BigQuery, dbt, Shopify, GA4, Looker Studio, Metabase 👉 Message me with a quick overview of your data setup.

Senior AI, Data & BI Full-Stack Engineer with 10+ years of experience delivering intelligent, data-driven platforms. I help companies transform raw data into powerful AI solutions, scalable data pipelines, and insightful BI dashboards that drive business decisions. From AI model development and LLM integrations to enterprise data architecture and full-stack analytics platforms, I deliver end-to-end solutions used by startups, SaaS companies, and enterprise organizations. I specialize in building production-ready AI systems, modern data platforms, and real-time analytics infrastructures. What I Can Help You Build AI & Machine Learning - Large Language Model (LLM) applications - Retrieval Augmented Generation (RAG) - AI agents & automation - NLP systems - Recommendation engines - Predictive analytics - Computer vision models - Model training, fine-tuning & deployment - AI SaaS products Tools: Python, PyTorch, TensorFlow, HuggingFace, LangChain, LlamaIndex, OpenAI API Data Engineering & Data Platforms - End-to-end data pipeline development - Data warehouse architecture - ETL / ELT pipelines - Real-time data streaming - Data lake implementation - Big data processing - Data governance & optimization Tools: Apache Spark, Airflow, Kafka, dbt, Snowflake, BigQuery, Redshift, Databricks Business Intelligence & Analytics - Executive dashboards - KPI reporting systems - Self-service BI platforms - Data modeling & semantic layers - Data visualization - Financial / operational analytics BI Tools: Power BI, Tableau, Looker, Superset, Metabase Full-Stack Data Applications - AI-powered SaaS platforms - Data APIs - Analytics web applications - Internal data tools - Backend systems for AI products Tech Stack: - Python, FastAPI, Django, Node.js - React, Next.js, TypeScript - PostgreSQL, MongoDB, Redis - Docker, Kubernetes, AWS, GCP, Azure Cloud & Infrastructure: - AWS, GCP, Azure - Terraform, Kubernetes, Docker - CI/CD, MLOps, DataOps Why Clients Work With Me: - Architect scalable AI and data platforms - Build production-grade systems (not just prototypes) - Clear communication and documentation - Enterprise-level security and performance optimization - Long-term technical partner mindset Example Projects: - AI knowledge assistant using RAG + LLM + vector databases - Real-time data pipeline processing millions of events/day - Enterprise Power BI analytics platform for financial reporting - ML model predicting customer churn with 92% accuracy - AI automation tools saving companies 100+ hours/month Industries Worked With: - FinTech - SaaS - Healthcare - E-commerce - Marketing Analytics - Logistics & Supply Chain Let’s Build Something Intelligent If you need help with: - AI product development - Data platform architecture - Machine learning systems - BI dashboards & analytics - End-to-end data infrastructure Send me a message and let's discuss your project.