Most companies don’t have a data problem They have a data architecture problem TBs of raw data sitting in pipelines that break, dashboards that lag, ML models that never make it to production, and AWS bills that grow faster than the infrastructure itself That’s where I come in I’m Shoaib, a Senior Data Engineer and AWS Solution Architect (SAA Certified) with 5+ years of experience building scalable data platforms, real-time pipelines, and AI/ML systems for healthcare, finance, and large-scale SaaS products I specialize in designing systems that process massive datasets, deliver reliable insights, and keep infrastructure costs under control Over the years I’ve helped companies: • Process TBs of healthcare and financial data using Spark, Kafka, and AWS data lakes • Build real-time streaming pipelines handling 1M+ requests/hour • Reduce cloud infrastructure costs by up to 50% through architecture optimization • Deploy AI/ML systems for healthcare prediction, stock forecasting, and medical transcription • Implement fault-tolerant data architectures on AWS following the Well-Architected Framework My work sits at the intersection of Data Engineering, Cloud Architecture, and AI/ML systems ------------------------------------------------------------------------------------------ Core expertise Solution Architecture AWS scaling, cost optimization, fault tolerance, CI/CD pipelines, cloud migrations Data Engineering Real-time streaming, batch pipelines, TB-scale data processing, CDC pipelines, CEP workflows, data lakes, governance, BI systems AI / ML Systems Predictive models, GenAI applications, RAG systems, domain-specific AI assistants ------------------------------------------------------------------------------------------ Tech Stack AWS (Glue, S3, EMR, Redshift, Athena, SageMaker, QuickSight) Apache Spark, Kafka, Flink, Hadoop, Hudi Snowflake, Postgres, MongoDB Python, SQL PyTorch, TensorFlow, LangChain, MLFlow ------------------------------------------------------------------------------------------ I’ve worked extensively with healthcare data (HIPAA compliant systems), financial time-series data, and large-scale event streaming platforms, helping teams turn messy data ecosystems into scalable, production-grade data platforms If you're looking for someone who can design the architecture, build the pipelines, and integrate AI/ML into real systems, I’d be happy to help ------------------------------------------------------------------------------------------ Keywords: Data Engineering, Big Data, Data Pipelines, ETL, ELT, Data Architecture, Data Lake, Data Warehouse, Real-Time Data Processing, Streaming Data, Batch Processing, Apache Spark, Apache Kafka, Apache Flink, Hadoop, Apache Hudi, Airflow, Apache NiFi, Snowflake, Snowpark, PostgreSQL, MongoDB, SQL, Python, Data Modeling, Data Governance, Data Quality, Master Data Management, CDC, Change Data Capture, CEP, Complex Event Processing, Data Integration, Data Migration, Data Analytics, Business Intelligence, Apache Superset, AWS QuickSight, Redshift, Athena, Data Visualization, AWS, AWS Architecture, AWS Solution Architect, AWS Cloud Architecture, AWS Cost Optimization, AWS Scaling, Fault Tolerant Systems, AWS Infrastructure, AWS Glue, AWS EMR, Amazon S3, AWS Redshift, AWS Athena, AWS Lambda, AWS CI/CD, Cloud Migration, Cloud Optimization, Distributed Systems, High Availability Architecture, Scalable Systems, Machine Learning, AI Engineering, AI Development, Generative AI, GenAI Applications, Agentic AI, Predictive Analytics, Model Training, Deep Learning, PyTorch, TensorFlow, Scikit-Learn, XGBoost, Time Series Forecasting, ML Pipelines, MLFlow, Feature Engineering, Model Deployment, AWS SageMaker, AWS Bedrock, LangChain, RAG, AI Chatbots, NLP, AI Automation.

Technical leadership and support of multi-disciplinary integration projects and enterprise-scale improvement initiatives Automation (IaC, GitOps) DevOps Solution architect SysOps / Site Reliability Engineer Full-cycle Platform Engineering and Administration Development and deployment of high-traffic UNIX/Linux-based services, platforms and infrastructure - both traditional datacenters and Public Clouds (AWS, GCP, OCI). Extensive background in Wireless and Wired Broadband T4elecommunication Control Plane Expertise: Traditional and Cloud Infrastructure enablement Solution architecture and system analysis Linux platform engineering and full lifecycle Automation via IaC (Terraform, Ansible Puppet) and CI/CD (GitlabCI, GitHub, Artifactory) Cisco Routing and switching and Network services Perl, Python, Bash, SQL, PL/SQL coding and scripting Containerized deployment - AWS EKS, Rancher k3s, Kubernetes (k8s) Interests: Cloud Native Function (CNF) solutions for Mobile Core Wireless Wired Convergence 5G Mobile Edge Computing (MEC) OpenRAN AI/Neuromorph PyTorch/TensorFlow IT Security / Infrastructure hardening

Senior Software Engineer & Architect with 20+ years of experience designing and delivering enterprise-level solutions across the full stack. Deeply proficient in both the .NET ecosystem (C#, ASP.NET Core, .NET Core) and the Java ecosystem (Java, Spring Boot, Spring MVC), as well as Node.js, Python, JavaScript, and TypeScript — with a proven track record of building scalable, high-performance systems for industries including fintech, retail analytics, and edtech. On the backend, I architect robust APIs and microservices using ASP.NET Web API, Spring Boot, Node.js, and FastAPI, design efficient data pipelines, and manage complex databases across SQL and NoSQL platforms (SQL Server, PostgreSQL, MongoDB, DynamoDB, Cosmos DB). On the frontend, I build clean, maintainable UIs with React and TypeScript/JavaScript, and use Python for data analytics, automation, and AI integrations. I'm an AI-native developer — I use Claude Code and Cursor daily to accelerate ticket throughput, reduce boilerplate, and ship faster. I have hands-on experience building LLM-powered applications using the Anthropic and OpenAI APIs — from prompt engineering and retrieval-augmented generation to integrating AI capabilities directly into production workflows. I can help your team adopt AI tooling, demonstrate what's possible, and get other developers up to speed quickly. I've also designed and implemented webhook-based automation pipelines that connect SaaS platforms, internal systems, and third-party services into cohesive, event-driven architectures. My cloud experience spans Azure and AWS, with a strong foundation in containerized deployments, infrastructure-as-code, and CI/CD automation. I have a strong passion for troubleshooting complex systems and diagnosing hard-to-find bugs — from race conditions in distributed services to memory leaks in long-running processes. I bring a methodical, root-cause-focused approach to debugging that resolves issues quickly and prevents recurrence. On the performance side, I've consistently delivered measurable gains: optimizing SQL queries and caching strategies to cut response times by 40%, profiling and tuning Java, Node.js, and .NET services under heavy load, and redesigning bottlenecked architectures to handle millions of transactions daily. I've led teams of up to 15 engineers, driven cloud-native transformations, and implemented DevOps practices with Docker, Kubernetes, Terraform, and CI/CD pipelines that cut release cycles by 50%. Whether greenfielding a new platform, modernizing a legacy system, or being called in to fix what others couldn't, I deliver reliable, well-tested code that scales with your business. Core strengths: - Full-stack development: Java · Spring Boot · C# · .NET Core · Node.js · Python · FastAPI · React · TypeScript · JavaScript - AI-native development: Claude Code · Cursor · Anthropic API · OpenAI API · RAG · AI-powered workflow automation · team AI adoption - Webhook & SaaS automation: event-driven architectures · third-party integrations · pipeline design - API & microservices architecture: REST · Spring Boot · ASP.NET Web API · Azure Functions - Troubleshooting, debugging & performance tuning: distributed systems · memory/CPU profiling · query optimization - Cloud & DevOps: Azure · AWS · Docker · Kubernetes · Terraform · CI/CD - Data: SQL Server · PostgreSQL · MongoDB · DynamoDB · Cosmos DB · ETL pipelines - Practices: TDD · code review · system design · team mentorship

Helping companies solve problems with Neo4j. Creating great ideas with LLM and Knowledge Graph, Cypher queries, and Graph Algorithms. I am an expert in Neo4j with extensive experience installing and configuring causal clusters and integrating them with other technologies such as Kafka and MongoDB. My main focus has been designing complex data architectures and optimizing data model performance in Big Data environments. I also have experience creating graph data models from scratch, building automatic matching tools using Cypher queries, and projecting Graph Algorithms and Knowledge graph creation for RAG applications. My primary goal is to help organizations make the most of Neo4j to improve their processes and provide innovative solutions (I)-[:LOVE]-(graphs)

I am a Senior Data Engineer with 10+ years of experience designing and implementing large-scale data pipelines, cloud data warehouses, and streaming solutions. I hold a proven track record of delivering high-performance, reliable, and cost-optimized data platforms for enterprises across multiple industries. 💡 Core Expertise: - Data Warehousing: Snowflake, Amazon Redshift - ETL / ELT: dbt, Python, Airflow, AWS Glue, Fivetran - Streaming & Messaging: Apache Kafka, Kinesis - Cloud Platforms: AWS (S3, Lambda, EC2, EMR, RDS, IAM, CloudFormation) - Databases & Querying: SQL, PostgreSQL, DynamoDB, MySQL - Big Data Tools: Spark, Hadoop (where relevant) ✅ What I Deliver: - Scalable data pipelines (batch & real-time) - Optimized Snowflake & Redshift architectures - ETL/ELT frameworks ensuring data quality & governance - AWS-based cloud data solutions with cost optimization - Kafka streaming integrations for real-time analytics ⭐ Why Hire Me? - 10+ years in data engineering & cloud ecosystems - 5-star reviews from clients on Upwork & Fiverr - Strong problem-solving, communication, and end-to-end delivery focus - Experience working with startups to Fortune 500 enterprises

As an accomplished Sr. Python, Data Scientist, ML,AI, I bring a wealth of hands-on experience in harnessing the power of data to drive strategic decisions and add substantial value to organizations. With a passion for transforming raw data into actionable insights, I excel in data analysis, visualization, and predictive analytics. My proficiency spans a wide range of tools and techniques, including Excel, R, Python, Tableau, machine learning, and deep learning Expereinced with LLMs. I have good hand on experience with different types large language models such as Zero-shot model, Fine-tuned or domain-specific models, Language representation model, Multimodal model My expertise in statistical analysis, multivariate testing, and text analysis empowers me to extract meaningful patterns from complex datasets. I've successfully built and interpreted various machine learning models, from Logistic Regression and Naive Bayes to Random Forests and Deep Neural Networks, delivering tangible results on real business data My commitment to innovation, strong work ethic, and effective communication skills make me a valuable asset for any organization. I am highly motivated to leverage my skills and diligence to drive data-driven decision-making, fuel growth, and achieve organizational objectives. If you're seeking a Python, Data Scientist, ML,AI who combines technical prowess with a passion for data-driven problem-solving, I'm here to help your organization thrive For the last 6+ years, I have been providing the following services: ✅ My services include: Python/Django Development AI/ML Development Data cleaning, analysis, and visualization Supervised learning (Classification / Regression) Time series analysis OpenAI,GPT3,4 NLP specialist Natural Language Processing (NLP) Computer Vision (CV) Python Selenium ,Scrapy for web scraping MEAN/MERN Development ✅ I am proficient in implementing Machine Learning Algorithms such as: Linear/Logistic Regression K-Nearest Neighbours (kNN) | Decision Trees | Support Vector Machine (SVM) Ensemble methods (Random Forest, XGBoost, CatBoost, AdaBoost, LightGBM, etc) Neural Network (ANN, RNN, CNN, DNN, etc) Transformers ✅ I use a variety of powerful tools, such as: Python,Django, Matplotlib, Seaborn, Pandas, Numpy, and Dask for data analysis and visualization SpaCy, Gensim, HuggingFaces, and NLTK for NLP tasks Scikit-Learn, Tensorflow, and Keras for implementing Machine Learning models Docker for containerization Let's meet and work together as a team

I help businesses build scalable data and AI systems from high-performance data pipelines to GenAI powered applications and analytics platforms on GCP, AWS, Azure, Microsoft Fabric, and Databricks. With 7+ years of experience in data engineering and cloud architecture, I specialize in designing data-intensive systems that process large-scale data efficiently and turn it into actionable insights and intelligent automation. 🔹 What I Can Help You With Cloud Data Engineering & Big Data Systems End-to-end ETL/ELT pipelines on GCP, AWS, Azure & Databricks BigQuery, Redshift, Synapse, Microsoft Fabric Lakehouse Apache Spark / PySpark (Databricks, distributed processing) GCP Dataflow, Pub/Sub, Cloud Functions, Composer (Airflow) AWS Glue, Lambda, S3 | Azure Data Factory & Synapse Batch & real-time streaming pipelines (Kafka, event-driven systems) Data modeling (star schema, lakehouse & warehouse architecture) GenAI & AI-Powered Data Applications LLM integrations (ChatGPT, Claude, Gemini) GenAI-based data pipelines & intelligent workflows Natural Language → SQL / data querying systems AI copilots, automation tools & internal assistants Recommendation systems (e-commerce, product analytics) Analytics & Data Products Product analytics (GA4, user behavior, funnel analysis) Marketing attribution & performance analytics Business intelligence & reporting systems Data-driven strategy & decision support solutions 🔹 What Makes Me Different I don’t just build pipelines I design end-to-end data platforms that connect data engineering, big data processing, and GenAI into real business use cases. My focus: Scalable architectures (handling high-volume data workloads) Cost optimization (BigQuery, Databricks, cloud-native systems) Clean, reliable data models for analytics and AI 🔹 Tech Stack GCP: BigQuery, Dataflow, Pub/Sub, Cloud Functions, Composer AWS: S3, Glue, Redshift, Lambda Azure & Fabric: Data Factory, Synapse, Fabric Lakehouse Databricks & Big Data: Apache Spark, PySpark Core: Python, SQL, Airflow, Kafka GenAI: ChatGPT, Claude, Gemini 🔹 Typical Projects I Work On Building scalable data pipelines (APIs, GA4, ERP → Data Warehouse/Lakehouse) Designing cloud-native data platforms (GCP, AWS, Azure, Databricks, Fabric) Developing GenAI-powered tools (chatbots, automation, data assistants) Creating real-time and streaming data systems Implementing recommendation engines and analytics platforms If you're looking for someone who can design and build a scalable data platform or AI-driven solution tailored to your business, let’s connect.

Data is powerful — but only when it’s usable. I help businesses design and build AI-ready data platforms — from raw data ingestion to real-time analytics and intelligent insights. With 11+ years of experience in Data and Cloud ecosystems, I specialize in: ✔ Scalable Spark & Databricks pipelines ✔ Lakehouse architectures (Azure / AWS) ✔ Real-time streaming (Kafka, Spark Streaming) ✔ ETL modernization (Talend, Informatica → Cloud) ✔ ML-ready data engineering foundations Whether you need: A new data platform built from scratch Migration to Databricks or Cloud Performance optimization Data pipelines for AI/ML use cases I focus on writing clean, production-grade, scalable solutions — not quick hacks. Clients describe me as reliable, detail-oriented, and easy to work with. If you're looking for someone who understands both engineering depth and business outcomes, let's connect.

I am 🏆 Certified Databricks (Associate & Professional) and 🏆 Microsoft Fabric & Azure Data Engineer with 8+ years of experience in ETL, leveraging Microsoft Azure technologies, Databricks, BigQuery, Microsoft Fabric, GCP, PySpark, SQL, MS SQL Server, Snowflake, and MySQL to deliver top-tier data solutions. My expertise spans a wide range of technologies and tools, ensuring seamless data movement, data scraping and transformation. I am skilled in orchestrating complex data workflows, automating pipelines, and streamlining ETL processes using AWS Glue, AWS EMR, Azure Data Factory, Databricks,Apache Airflow, SSIS Pentaho, Talend, Informatica etc. I excel at integrating with top-tier data warehouse platforms such as Snowflake, Redshift, Azure Synapse Analytics, and BigQuery, building robust ETL pipelines while managing data lakes on ADLS, S3, Databricks Lakehouse Platform and GCS. 🏆 Key Areas of Expertise: 📌 Development Skills: Databricks, Unity Catalog, Lakeflow, Kafka, Airflow, Airbyte, MS-SQL Server, Power BI, Tableau, Qlik, Apache Superset, Azure Data Factory, MySQL, ETL, Job Scheduling and Automation, Query Optimization etc. Performance Tuning 📌 Programming Languages: Python, SQL, PySpark 📌 Databases: SQL Server, PostgreSQL, MySQL, DynamoDB, Amazon RDS 📌 ETL Tools: AWS Glue, AWS EMR, Azure Data Factory, SSIS, Apache Airflow, Pentaho, Talend, Informatica. 📌 Data Scraping: Expertise in Python, Selenium, Playwright, Puppeteer and BeautifulSoup. 📌 Data Warehouse Platforms: Azure Synapse Analytics, Redshift, BigQuery, Snowflake 📌 Data Storage Services: Amazon S3, Azure Data Lake Storage (ADLS), Google Cloud Storage (GCS), Databricks File System (DBFS) 📌 Big Data Technologies: Hadoop, Hive, HBase 📌 Workflow Orchestration: Apache Airflow, Azure Data Factory 📌 Data Lake Management: Delta Tables, Delta Live Tables, Data Flows, Jobs 📌 Visualization Tools: Power BI, Tableau, Superset 📌 IDE’s: Databricks, SQL Server Management Studio, DBeaver, Snowflake, Azure Data Studio 📌 Cloud Platforms: Azure, GCP, AWS, Snowflake. Our comprehensive skill set, and hands-on experience make us adept at tackling any data engineering challenge thrown our way.

Certified TOGAF 9 Enterprise Architect with over 18 years of IT service experience, specializing in solution architecture, innovation, consulting, and leading diverse projects. My extensive background in IT services has honed my skills in consulting, architecture, and software development. I am now focused on leveraging these skills in AI, Machine Learning, Data Lakes, and Analytics, seeking opportunities that challenge me to continue learning and applying cutting-edge technologies in real-world applications. Recent Projects and Specializations: Artificial Intelligence & Machine Learning: Developed several generative AI projects including: A solution for manufacturing operators that provides real-time fixes based on user-generated prompts and descriptions. An AI-driven healthcare lab assistant that suggests diagnostic tests based on user inputs. Advanced ML algorithms for monitoring pH levels in sugar production, crucial for maintaining quality control over product consistency. Implemented an ML model for HVAC systems that predicts power consumption spikes and potential breakdowns, enhancing maintenance efficiency and energy management. Data Science & Big Data: Expertise in handling large-scale data environments from terabytes to petabytes, developing actionable insights across multiple domains including Retail, Finance, Manufacturing, IoT, and Healthcare. Proficient in: Apache Hadoop, Spark, Cloudera CDH, Hortonworks, MapR Real-time data processing with Apache Hive and Elasticsearch Cloud Architecting & Data Lakes: Skilled in designing and implementing robust cloud solutions and data lakes that streamline data accessibility and analysis, supporting high-level decision-making processes. Business Intelligence & Analytics: Experienced in integrating BI tools and technologies like Splunk, Tableau, and OBIEE to transform raw data into valuable business insights. Industry Expertise: Telecom, Retail, Banking & Financial Services, Utilities, Education