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👋 I am new to Upwork, but not new to the work. I have 8+ years of real production experience, and I take every project seriously. I build data systems, AI pipelines, and automation workflows that work reliably at scale.😎 I am a Senior Data Engineer and AI Integration Specialist with 8+ years of experience. I do not just move data from one place to another. I design systems that turn complex and messy data into clean, useful information and build automation that saves teams hours of manual work every week. 🧠 Tech stack: Python, SQL, PySpark, AWS, Snowflake, BigQuery, Databricks, PostgreSQL, Airflow, dbt, Docker, FastAPI, n8n, Claude API, OpenAI, LangChain, Playwright, Supabase, Airtable, Salesforce, GoHighLevel 💡 What I bring: • Pipelines that process 100M+ records every month • Up to 70–80% reduction in manual reporting • AI and LLM integrations that automate real business workflows • Web scraping systems that collect and enrich data at scale • Strong focus on data quality, testing, and stability • Solutions that are easy to support and scale ⚙️ What I do: • Build data pipelines from APIs, databases, and files • Design data models and warehouse architectures • Work with cloud platforms: AWS, BigQuery, Snowflake, Databricks • Set up orchestration with Airflow, Prefect, and dbt • Build AI agents and RAG systems using Claude and OpenAI APIs • Automate workflows with n8n, Make, and custom Python scripts • Build web scrapers with Playwright, Scrapy, and BeautifulSoup • Integrate CRMs: Salesforce, HubSpot, Airtable, GoHighLevel • Create dashboards in Power BI, Tableau, Looker, Metabase, and Retool Experience: ▶️ eCommerce: 100+ data sources, product datasets, marketplace integrations ▶️ FinTech: data pipelines, financial reporting, regulated environments ▶️ Healthcare: data cleaning and structuring for analysis and reporting ▶️ Real Estate and PropTech: pricing models, permit data pipelines ▶️ Government: automated document and data processing ▶️ Migrations: legacy SQL and Excel to modern cloud platforms 🚀 If you need reliable data infrastructure, AI automation, or clean analytics, I can help.

👋 Hi, I’m a 🏆 ⭐️⭐️⭐️⭐️⭐️Top Rated Python Data Engineer & Data Visualization Expert at GroupBWT - a 100+ person data engineering company and official AWS, Snowflake & Databricks partner, building enterprise data systems since 2009. As a Python Big Data Engineer, I specialize in designing scalable data systems. My role as a Big Data Engineer is focused on building reliable pipelines, automation, and analytics infrastructure. Every Python Data Engineer decision I make is oriented toward scalability, performance, and data reliability. I work as a Big Data Engineer and Python Data Engineer on enterprise-grade systems where architecture matters for both ingestion and transformation layers. As a Data Engineer, I ensure that raw data becomes structured, usable, and ready for business intelligence. Here’s how I support our clients as a Python Big Data Engineer: ✅ Our ETL pipelines process over 100 million records monthly across major cloud data warehouses
 ✅ My solutions reduce manual reporting effort by up to 80% through end-to-end automation
 ✅ We build Python Data Engineer workflows for integrating and transforming complex datasets ✅ Every pipeline is tested and quality-checked to meet enterprise data standards 🔁 What I Do as a Python Azure Data Engineer and azure data engineer ⚙️ Data Engineering (Python AWS Data Engineer Core Work) 🔹 API & event-based ingestion using Python Data Engineer best practices 🔹 Python + SQL transformations 🔹 Data modeling, schema design, enrichment 🔹 ETL/ELT into Snowflake, Databricks, BigQuery with Python Data architecture 🔹 Monitoring, retries, observability & data quality testing for Python Data pipelines 🔹 CI/CD for pipelines & cloud cost optimization as a Python Data Engineer Platforms I’ve delivered as a Python Data Engineer process 100M+ records/month, integrate 30–80+ APIs, and power real-time BI environments. 📊 Data Visualization & BI (Python gcp Data Engineer Perspective) 🔹 I bridge raw data with business decisions as a Python gcp Data Engineer 🔹 Power BI, Looker Studio & Tableau dashboards connected by Python GCP Data Engineer pipelines 🔹 Executive KPI reporting built by a Python AWS Data Engineer 🔹 Semantic layer & metric standardization in Python Data Engineer systems 🔹 Real-time reporting (<5 min latency) enabled by Python Data Engineer architecture 🔹 BI performance optimization from a Python Data Engineer point of view 🔹 Data storytelling for leadership & operations powered by Python Data Engineer workflows My solutions as a Python Data Engineer reduce manual reporting effort by up to 70-80% and significantly improve forecasting accuracy. 🧩 Recent Experience (Python Data Engineer and Machine Learning Projects) 🔹 Retail & eCommerce Data Warehousing (Python Data Engineer) Built ingestion + normalization pipelines for 120+ eCommerce sources, syncing ~500K SKUs/day into Snowflake / BigQuery using Python Data Engineer architecture. 🔹 FinTech Ingestion & Reporting Layer (Python Data Engineer ) Delivered automated pipeline pulling from 30+ sources (APIs, DBs, files), built with Python Data Engineer logic for validation, transformation, and reporting. 🔹 Government ETL & Document Processing (Python Azure Data Engineer | Data Analyst) Automated processing of 10K+ documents/day using Python Azure Data Engineer workflows and Machine Learning: extraction, classification, mapping, and database loading. 🔹 Healthcare Data Normalization & Compliance (Python AWS Data Engineer | Data Analyst) Cleaned millions of records using Python AWS Data Engineer pipelines with Machine Learning, schema mapping, PII-aware handling, and reproducible transformations. 🔹 Large-scale Cloud Migrations (Python Data Engineer | Data Analyst) Migrated legacy systems into BigQuery/Snowflake using Python Data Engineer architecture with Machine Learning, incremental loads and automated pipelines. 💻 Tech Stack (Python Data Engineer | Data Analyst Toolkit) ⚙️Languages: Python, SQL, DAX, Power Query, PySpark, Scala, Bash/Shell, JavaScript, etc.
 ⚙️Data Engineering & Processing: PySpark, dbt, Airflow, Prefect, CDC, REST & GraphQL, etc.
 ⚙️Data Warehouses & Databases: Snowflake, Databricks, BigQuery, AWS, PostgreSQL, MSSQL
 ⚙️Cloud Platforms: AWS: S3, Glue, Lambda, CloudWatch, Athena, Redshift, BigQuery, Dataflow
 ⚙️Data Modeling & Architecture: Star schema, Snowflake schema, Lakehouse architecture, etc.
 ⚙️Monitoring & Data Quality: dbt, Prometheus, Grafana, AWS CloudWatch, GCP Monitoring, etc.
 ⚙️BI & Visualization: Power BI (Desktop, Service), Tableau, Looker Studio, Metabase, etc.
 ⚙️DevOps & CI/CD: Git, GitHub, GitLab CI, Docker, Terraform, etc. 🚀 If you need automated pipelines, clean data models, and executive-level dashboards - as a Python Data Engineer and Data Analyst I can help you build a robust system from end to end. ➡️ Invite me to your job and let’s design a scalable data strategy with a Python Data Engineer leading the way. Last updated June 15, 2025

Need an AI pipeline or data platform built for production - not just a prototype? I ship end-to-end AI and data systems that handle real scale: 1M+ documents, 100+ production pipelines, 10x costs optimization. 12+ years building for DraftKings, DataRobot, Sift, and Sentra. Now I help companies turn AI proof-of-concepts into production systems that actually work. Recent solutions & projects: - Built QA framework and developer tooling for AI-powered lease extraction platform - test infrastructure for validating LLM extractions across 19 lease term categories (with 92+ test cases), plus an internal web tool for debugging, prompt reconstruction, and one-click test case generation. - Built a custom EOR (Employer of Record) classification rules engine with LLM-generated rationales, and a conversational AI assistant in front of it that turns a plain-English scenario into a recommendation while the deterministic engine stays the source of truth. - Built AI-powered search API with hybrid vector+semantic ranking (1M+ CV files across 6 brands) - Re-engineered 100+ ETL pipelines - 10x infrastructure cost reduction - Conversational analytics platform: natural language to business insights for logistics What I Build: 1. RAG & Knowledge Systems Production pipelines, vector database optimization (Azure AI Search), hybrid search with reranking, custom embeddings for domain-specific retrieval 2. LLM Integration OpenAI, Anthropic, Azure OpenAI - function calling, structured outputs, agent orchestration, prompt engineering for consistent results. Frameworks: LangChain and Microsoft Agent Framework. 3. Backends & Data Platforms FastAPI, async Python, cloud-native on AWS/Azure/GCP, data warehouses (Snowflake, BigQuery, Databricks), real-time and batch pipelines. Tech Stack: Python, FastAPI, Docker, Kubernetes, Terraform, AWS/Azure/GCP, Databricks, Snowflake Industries: Financial Services, Telecom, Data Security, Logistics, Legal, Recruitment

Hello! Thank you for visiting my profile. I am a Manual QA Engineer with experience in testing web and mobile applications. I help identify bugs, test functionality, and ensure that software works correctly and smoothly for users. My experience includes functional testing, regression testing, API testing, and detailed bug reporting. I work carefully with requirements and always focus on accuracy and clear documentation. I also have experience with data entry, web research, and information processing. I am reliable, detail-oriented, and always focused on delivering high-quality results. I will be happy to help you with your project.

I am a QA Engineer with over 4 years of experience in manual testing, automation and quality assurance. I have worked with UI, API and design testing, created test cases in Gherkin, analyzed them through Jenkins and interacted with development teams and product owners. I use tools like Jenkins, Jira, Confluence, Zephyr, IDEA, Postman, Mailtrap, Miro, Figma, GCloud, Swagger. I help find critical bugs before release to ensure the product is stable and safe for users. I have experience in fast and accurate data entry, which saves the team time and reduces the risk of errors. I also perform transcription and annotation, ensuring high-quality processing of information for clients. My work combines attention to detail with a practical understanding of business goals, so I can be useful in both testing and data or content management tasks.

🤖 I design AI systems · Workflow Automation · cloud data platforms & reporting architecture for companies that need reliable operations instead of disconnected tools As an AI Solutions Architect I connect n8n · Make · Zapier · Microsoft Power Automate · OpenAI API · Claude API · Azure OpenAI · Python · REST API · Webhooks · databases · Snowflake · Azure Data Warehousing & Power BI My work combines three layers AI Automation Data Integration Cloud Architecture I help when a team has manual processes between CRM platforms · ClickUp · Airtable · HubSpot · Notion · Google Sheets · internal tools · databases · APIs & reporting systems I design the full path from business process to Workflow Automation to API Integration to Database Integration to AI Agent Development to Error Handling and Monitoring to Dashboard Automation Typical projects include ▪ AI Agent Development for internal operations · support · analytics · document processing · knowledge search & repetitive tasks ▪ n8n AI Agents connected to OpenAI API · Claude API · Azure OpenAI · LangChain · Supabase · REST API · Webhooks & company data ▪ RAG Systems · AI Chatbots · Conversational AI & company knowledge workflows ▪ AI Workflow Automation for approvals · notifications · enrichment · validation · routing · synchronization · reporting & human review ▪ Business Process Automation with n8n · Make · Zapier · Microsoft Power Automate · Google Apps Script & Python ▪ CRM Automation · ClickUp Automation · lead routing · task creation · pipeline updates · reminders & reporting ▪ API Integration · Third-Party Integration · Data Integration · Database Integration · REST API workflows & custom Webhooks ▪ ETL Automation · Data Extraction · Data Transformation · Scheduled Workflows · monitoring · recovery logic & documentation ▪ Power BI Automation · Dashboard Automation · Automated Reporting · KPI logic · Data Modeling & reporting-ready databases I do not choose a tool before understanding the process n8n supports flexible Workflow Automation · self-hosted systems · custom logic · AI Agent Development & complex API Integration Make supports fast business integrations · visual workflows · SaaS connections · CRM Automation & operational prototypes Python supports Workflow Automation that requires custom algorithms · advanced Data Transformation · scale · testing or deployment control Before development I define business rules · workflow states · data ownership · access permissions · human approvals · exception handling · monitoring · retries · audit logic · deployment structure & reporting requirements A strong AI solution needs trusted data · secure Database access · clear Solution Architecture · reliable API Integration · controlled Workflow Automation · monitoring · documentation & measurable business output My architecture background includes Azure Data Warehousing · Snowflake Database · Azure Data Factory · Azure DevOps · Databricks Platform · Microsoft Azure SQL Database · Microsoft SQL Server · ETL · Data Modeling · Business Intelligence & Microsoft Power BI For Azure projects I design Azure Cloud Architecture · Azure Data Warehousing · Azure Data Factory pipelines · Azure DevOps delivery · CI/CD · Terraform · Git · deployment control & Azure OpenAI integration For Snowflake projects I work with Snowflake Database architecture · Snowflake Data Warehousing · Data Integration · ETL Automation · dbt workflows · reporting layers · access logic · performance review · cost control & Power BI connectivity One enterprise Azure engagement included scalable multi-tenant architecture · strict data isolation · Azure Databricks processing · infrastructure cost reduction & multilingual Power BI reporting Another long-term engagement expanded from Power BI reporting into automated data validation · incremental refresh · data reliability improvements & third-party service integration I connect AI Automation to the data foundation I connect reporting to reliable ETL and Database Architecture I work across Automation Architecture · Solution Architecture · Cloud Architecture · Cloud Data Architecture · Database Architecture · AI Solution Architecture & AI Data Architecture If your AI Agent cannot access trusted company data I can design the Data Integration and Database Integration layer If your Workflow Automation fails without visibility I can add Error Handling and Monitoring · retries · alerts · audit logic & recovery workflows If your reporting depends on manual exports I can connect ETL Automation · Azure Data Warehousing · Snowflake Database · Power BI Automation & Automated Reporting If your prototype needs to become a production system I can define the Solution Architecture · security model · data flow · deployment process · monitoring structure & technical roadmap Send me your process · tools · data sources & expected outcome 🏆 Wait, you’ve actually made it to the very end! Mention "1 in 100" in your first DM and I will provide a discount😉