Hire the Best Snowflake Professionals

Struggling to unlock value from your data or build scalable, high-performance analytics platforms? I’m 𝑯𝒂𝒔𝒆𝒆𝒃 𝑨𝒔𝒊𝒇,a Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP, I build high-performance data pipelines, cloud data platforms, and real-time analytics solutions. Experienced in data warehousing, cloud integration, machine learning workflows, and performance optimization to transform raw data into actionable business insights. Let’s build reliable, scalable, and data-driven solutions for your business growth. I’ve successfully completed 99+ projects across industries, designing ETL pipelines, MLOps workflows, Delta Lake architectures, and cloud analytics solutions on AWS, Azure, and GCP. ✔️ 𝑯𝒐𝒘 𝑰 𝑯𝒆𝒍𝒑 𝑩𝒖𝒔𝒊𝒏𝒆𝒔𝒔𝒆𝒔 𝑻𝒓𝒂𝒏𝒔𝒇𝒐𝒓𝒎 𝑫𝒂𝒕𝒂 𝒊𝒏𝒕𝒐 𝑰𝒏𝒔𝒊𝒈𝒉𝒕𝒔 ➜ Databricks & Big Data Engineering I specialize in designing enterprise-grade Databricks Lakehouse architectures and Delta Lake solutions. My expertise in Spark and PySpark allows me to build high-performance pipelines for both batch and real-time analytics, ensuring your data infrastructure is robust and scalable. ➜ Machine Learning & MLOps With a focus on machine learning and MLOps, I build and deploy predictive models using tools like MLflow and TensorFlow. I automate end-to-end ML pipelines to enhance efficiency and accuracy, driving impactful insights from your data. ➜ Cloud & Data Platforms I implement secure, scalable cloud solutions on platforms like AWS, Azure, and GCP. My experience includes cloud migration, Kubernetes, Docker, and CI/CD automation, ensuring seamless integration and optimal performance. ➜ ETL & Data Pipelines I develop reliable ETL processes and data pipelines that streamline data integration and transformation. My work with streaming analytics using Kafka and Spark ensures real-time data processing and actionable insights. ➜ Data Analyst & Visualization I create actionable dashboards and visualizations using Power BI, Tableau, and Databricks SQL. My focus is on driving KPI reporting and business intelligence to support strategic decision-making. ➜ Snowflake I leverage Snowflake's capabilities to build efficient data warehousing solutions, optimizing data storage and retrieval for enhanced performance and scalability. ➜ Python My proficiency in Python allows me to develop complex data processing scripts and machine learning models, ensuring robust and efficient data handling. ➜ NLP (Natural Language Processing) I apply NLP techniques to extract meaningful insights from unstructured data, enabling advanced text analytics and improved decision-making processes. ➜ GCP (Google Cloud Platform) I utilize GCP's powerful tools to design and deploy scalable cloud solutions, ensuring high availability and performance for your data-driven applications. ➜ Data Warehouses I design and manage data warehouses that provide a centralized repository for your data, facilitating efficient data analysis and reporting. ✔️ 𝑲𝒆𝒚 𝑻𝒐𝒐𝒍𝒔 & 𝑻𝒆𝒄𝒉𝒏𝒐𝒍𝒐𝒈𝒊𝒆𝒔 ▪ Databricks & Big Data: Databricks, Delta Lake, Apache Spark, PySpark, Unity Catalog, Kafka, Hadoop, Real-time Streaming ▪ Machine Learning: MLflow, TensorFlow, PyTorch, scikit-learn, Feature Store, Predictive Analytics, NLP ▪ Cloud Platforms: AWS, Azure, GCP, Kubernetes, Docker, CI/CD ▪ Analytics & BI: Power BI, Tableau, Databricks SQL, KPI Dashboards, Data Strategy ▪ Data Engineering: ETL Pipelines, Data Lakes, Data Warehousing, Data Migration, Performance Optimization ✔️ 𝑾𝒉𝒚 𝑪𝒉𝒐𝒐𝒔𝒆 𝑴𝒆 I combine deep technical expertise with practical business understanding, delivering scalable, cost-efficient, and AI-ready data solutions. My goal is to turn your data into a strategic asset that powers smarter decisions and measurable growth. Let’s collaborate to build your next-generation analytics platform and unlock the full potential of your data. Check my portfolio for architecture samples, dashboards, and case studies. Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Azure Databricks, GCP Analytics, ETL Developer, Data Analytics, Delta Lake Expert, Machine Learning Engineer, Python, Database Architecture, Data Processing, ETL, Big Data, Database Design, Data Engineering, Data Analytics & Visualization Software, Data Visualization, Deep Learning Modeling, Data Warehousing & ETL Software, Snowflake, Amazon Web Services, ETL Pipeline, Machine Learning, Deep Learning, Data Science, Data Analysis, Cloud Engineering, Artificial Intelligence, Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP

⭐⭐⭐⭐⭐ 5.00 across 200+ Jobs🥇𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗼𝗻 𝗧𝗮𝗯𝗹𝗲𝗮𝘂 (𝗗𝗲𝘀𝗸𝘁𝗼𝗽 𝗦𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘀𝘁) 🥇𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗼𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 (𝗣𝗟𝟯𝟬𝟬 💎 Top Rated PLUS, Trusted by 200+ clients, 9800 + 🅷🅾🆄🆁🆂 worked, )High-quality outcomes & your trusted companion for the long-term data journey. 12+ Yrs of immense ex 🏅 Top 1% of Tableau Developers 🏅 Top 1% of PowerBI Developers 🏅 Top 1% of Sigma computing Developers Open for a long-term opportunity 15+ years of immense experience in building 200+ solutions and implementing in QlikView Domo, Klipfolio, and Tableau, Power BI projects single-handedly. I also have sound knowledge of ETL, Datamining, data fetching, Oracle database, Google Analytics, Social media analytics. I am also Tableau sales accreditation certified and attended tableau basic and advanced paid training certification as well. I also have snowflake core certification, and also Klipfolio certified expert, please visit my certification section for more info. Skillset: ✅ Tableau ✅ Klipfolio ✅ Qlikview ✅ Domo ✅ Google data studio ✅ Sisense ✅ Looker ✅ Power BI ✅ Click data ✅ AWS Quick sight ✅ Google analytics ✅ Tealium ✅ Airtable ETL Tools: ✅ Azure DataFactory ✅ AWS Glue ✅ Alteryx ✅ Integromat/Make ✅ Knime ✅ Power Automate Databases: ✅ SQL Server ✅ Oracle ✅ Hadoop impala/hive ✅ Mongo DB ✅ Postgres Sql ✅ Snowflake/Amazaon RDS 💎 Top Rated PLUS | 🕐 Fast Turnaround 🌟WHY CHOOSE ME OVER OTHER FREELANCERS? 🌟 ✅ Client Reviews ✅ Communication ✅ Mastery 🟢 GO GREEN 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸🟢 Cloud: Azure (Data Factory, Synapse, Fabric), GCP (BigQuery, Dataflow), AWS Languages: Python, SQL, R, Scala, DAX, JavaScript Orchestration: Airflow, dbt, Prefect, Kafka, CI/CD, Git BI: Power BI, Looker Studio, Tableau, QlikView, Excel/Power Pivot AI/Automation: Clawdbot, Moltbolt, Openclaw, LangChain, n8n, Make, Zapier, Pinecone CERTIFICATIONS 🏅 Tableau Desktop Specialist Certified 🏅 Tealium Specialist Certified 🏅 Microsoft Certified: Power BI Data Analyst 🏅 Google Data Studio Certified 🏅 Alteryx Designer certified 🏅 Microsoft Certified Professional (MCP SQL) 🏅 Excel and Spreadsheets Expert 🏅 Zoho and Looker Expert 🏅 D365 CRM and SharePoint Expert 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗜'𝘃𝗲 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱: - Engineered ETL pipelines processing 50M+ events/day across GCP, Snowflake, and BigQuery - Delivered a $47K enterprise AI + web application rated elite by the client - Replaced manual reporting workflows saving teams 20+ hours per week - Scaled Power BI datasets from thousands to 10M+ rows without performance loss - Built AI document parsing systems handling enterprise-grade extraction and classification - Designed Snowflake data warehouses with optimized dimensional models for executive reporting 𝗣𝗶𝗹𝗹𝗮𝗿 𝟭: 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 & 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 ETL/ELT architecture, real-time ingestion, CDC patterns, incremental loads, and warehouse modeling. I work across Snowflake, BigQuery, Databricks, Azure Data Factory, dbt, Airflow, and Kafka. Clean data contracts, reliable refreshes, and systems your team can maintain. 𝗣𝗶𝗹𝗹𝗮𝗿 𝟮: 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 & 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 (𝗔𝗟𝗟 𝗧𝗼𝗼𝗹𝘀) Power BI (semantic models, DAX, embedded analytics, Power BI Service, Fabric), Looker Studio, Tableau, QlikView, and Excel/Power Pivot. From KPI frameworks and dimensional modeling to real-time executive dashboards I build reports that are fast, accurate, and aligned to decisions. Performance tuning for slow or bloated reports is a core specialty. 𝗣𝗶𝗹𝗹𝗮𝗿 𝟯: 𝗔𝗜, 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 & 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 Production-grade LLM integration using Clawdbot, Moltbolt, Openclaw, LangChain, and RAG architectures. Custom AI agents with guardrails, human-in-the-loop controls, and monitoring for enterprise safety. Workflow automation through n8n, Make, Zapier, Langflow, Flowise, and SimStudio — connecting AI to your CRM, ticketing, email, Slack, and internal systems with role-based access and audit trails. Typical AI deployments: AI support agents, document intelligence pipelines, internal ops copilots, knowledge search with permissions, and intelligent lead qualification systems. 𝗦𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀: Healthcare (EHR, operational analytics, HIPAA-compliant reporting) Finance & Enterprise (P&L, KPI dashboards, multi-source consolidation) SaaS & Startups (product analytics, embedded BI, growth pipelines) 𝗠𝘆 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵: Every engagement starts with a short audit current-state review, data access, KPI definitions, and a milestone delivery plan with clear timelines. Then we build in iteration cycles with hardening, documentation, and handover so your team owns the system when I'm done. I always leave things better than I found them. Proper data models, clean logic, version-controlled code, and documentation your team can actually work with. Have a project in mind? Click "Invite to Job" let's talk.

🤖 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😉

I build data platforms that work at scale and keep working as your business grows. Over the past 10 years I've served as the lead or founding data engineer across fintech, e-commerce, ride-hail, legal tech, and cybersecurity companies. That means I've designed systems from scratch, made architecture decisions with no one to fall back on, and delivered platforms that product teams actually use. Here's what I typically get hired to do: → Build greenfield data platforms on AWS or GCP from the ground up → Design and ship production ETL/ELT pipelines (Airflow, Dagster, dbt) → Set up scalable warehouses and governance (Snowflake, BigQuery, Redshift) → Implement real-time streaming pipelines (Kafka, Spark Streaming, CDC) → Build AI-powered data applications (RAG, LLMs, LangChain, vector DBs) → Fix broken or unreliable pipelines and make them production-grade → Architect cloud infrastructure on AWS, GCP, Azure (Terraform, Kubernetes) Recent work includes: - Led data platform engineering for a US e-commerce company processing billions of events daily. I re-architected ingestion pipelines, built Snowflake governance from scratch, introduced Prometheus monitoring and CI/CD standards across the platform. - Built a full data platform on GCP (BigQuery, Dataproc, Airflow) for a music streaming company. Firebase, AppsFlyer, and app store data all flowing into one warehouse within weeks. - Designed an AWS data platform for a ride-hail company managing 500+ streaming and 700+ batch jobs — including a self-serve portal that replaced multi-step CLI workflows for engineers. - Built a legal AI search engine using LangChain, Pinecone, and RAG — full pipeline from document ingestion to LLM-generated answers, deployed on AWS with auto-scaling. - Built an AI inventory insights agent for a US automotive company — multi-source data pipelines, real-time APIs, conversational interface. I work in English daily, communicate proactively, and deliver production- ready code — not prototypes. I'm used to working directly with CTOs and technical leads in US and European time zones. Tools I work with regularly: Python · SQL · Airflow · Dagster · dbt · Snowflake · BigQuery · Spark · Meltano · Kafka · AWS (S3, EMR, Glue, ECS, Lambda, EC2, EKS) · Databricks · GCP · Azure Terraform · Docker · Kubernetes · LangChain · FastAPI · MLflow · Weaviate, Celery If you're building a data platform, fixing one, or adding AI/ML capabilities to your stack, let's talk.

Messy data slowing your team down? I build scalable ETL/ELT pipelines and modern cloud architectures on Azure, Databricks, Fabric, and Snowflake that turn raw, chaotic data into clean, analytics-ready systems fast and reliably. I bridge the gap between fragmented data sources and production-grade dashboards, seamlessly adapting to your existing infrastructure rather than forcing an expensive rebuild. What I Can Help You With: Data Warehouse & Lakehouse Architecture: Implementing Medallion design patterns (Bronze → Silver → Gold) using Delta Lake, Microsoft Fabric OneLake, and Snowflake. Scalable ETL/ELT Ingestion: Building automated, metadata-driven pipelines via Azure Data Factory, Fabric Pipelines, Databricks (PySpark/SQL), and dbt. Real-Time Data Streaming: Architecting low-latency workflows using Apache Kafka, Azure Event Hubs, and streaming engines. Database Design & Optimization: Performance tuning, indexing, and data modeling for PostgreSQL, Azure SQL, and cloud warehouses. Proven Project Highlights: Microsoft Fabric Incremental Pipeline: Built a control-table pattern using Get Metadata, Lookup, and ForEach loops to orchestrate zero-duplicate, quarterly ingestion from SharePoint into OneLake via Dataflow Gen2. Azure/Databricks Streaming: Developed a restaurant analytics platform processing 80,000+ events/day, cutting reporting lag from 6 hours to under 3 minutes. Kafka/Snowflake Pipeline: Engineered a real-time stock market data pipeline tracking 120+ tickers with under 8 seconds end-to-end latency. I write clean, documented code your team can maintain long-term and provide transparent daily updates. Message me with your data challenge and I’ll walk you through exactly how to solve it.

I build BigQuery warehouses, dashboards, and increasingly the AI and LLM layer that goes on top of them. For the last six years I've consulted for companies ranging from big-box retailers to Y-Combinator tech startups to help them get out from under manual reporting and scattered data. Most recently I've been building RAG systems and LLM observability for industrial SaaS applications, alongside the BigQuery, executive dashboards, and data engineering work (ETL) that has been my main lane for years. What I help clients build: • RAG and LLM systems. Production RAG over your business data (Claude, Gemini, GPT, vector stores), prompt and retrieval evaluation, dashboards for LLM cost, latency, and accuracy, and agentic workflows that connect tools to action. • BigQuery warehouses and ETL. Schema design, partitioning, cost cleanup, plus Python pipelines that ingest from Quickbooks, Stripe, GHL, HubSpot, GA4, Shopify, Filevine, and a long list of custom APIs. HIPAA-compliant when it needs to be. • Dashboards that actually get used. Looker Studio, Metabase, and ThoughtSpot (avoid PowerBI and Tableau like the plague). I always prototype the dashboard, so you see the end result first, we don't build pipelines you don't need, and I can give you a fixed-price quote (most freelancers will never give fixed-price quotes). • Internal tools and automations. Cloud Functions, Cloud Run, Slack and email integrations, Stripe billing, scheduled syncs. Things that should just run quietly in the background and stop being someone's manual job. A few things to know about working with me: I've hired freelancers on Upwork myself, so I know the difference between someone who hides behind their service and someone who moves the business forward. I write SQL and Python the next engineer can read without a guide. I'll tell you when the fancy version of a thing isn't worth building. I prefer working off real data and screenshots over abstract requirements docs. I have adopted AI tools that help me to complete data projects in 7 days by myself that used to take me 12 weeks with a small team.