🥇 Top Rated Plus Data Architect & Engineer 🎯 Providing Decision Clarity via Automated Data Infrastructure Hi, I’m Farhan! Over the past three years, I’ve specialized in architecting data infrastructure and connected decision systems that give executives and business leaders a real-time, clear picture of their company’s performance, operations, and financials. During my tenure at Requin Analytics, I focused on engineering executive-level systems that integrated directly with company warehouses and cloud platforms—allowing leaders to track live logic through automated data pipelines. Having served global firms ZigTech Solutions, I’ve delivered results for founders and directors across E-commerce, SaaS, manufacturing, healthcare, logistics, and construction. As a Top Rated Plus Talent on Upwork, I focus on technical strategy for startups and growing enterprises, creating scalable architectures curated to match specific business growth goals and complex data requirements. 🥇 Here’s How I Can Help Your Business: 🎯 Decision Systems & Executive Intelligence • Executive & C-Suite Decision Systems • Automated Profit and Cash Flow Logic • Strategic KPI & Performance Architecture • E-commerce & Marketing Intelligence • Operational & Departmental Infrastructure • Custom-built systems based on your company’s unique requirements 🎯 Data Engineering & KPI Architecture • Automated data pipelines connected to cloud warehouses (BigQuery/Snowflake) • Centralized "Source of Truth" through dbt modeling and SQL optimization • Scalable KPI setups with accurate logic and high-speed performance • End-to-end data integration for better organizational visibility 🎯 Infrastructure Management & Strategy • Manage data roles, permissions, and security protocols • Optimize system performance and logic reliability 🛠 Tools I Work With Engineering: SQL, dbt, BigQuery, Snowflake, Power Query Intelligence: Power BI, Tableau Automation: Power Automate, Microsoft 365 Collaboration: ClickUp, SharePoint, Slack 🔍 How I Work 1️⃣ Discovery Call: I’ll discuss your business goals and the specific logic needed for your decision systems. 2️⃣ Architecture First: I’ll design the data flow and logic mapping before deployment, ensuring the system is built for scale. 3️⃣ Engineering & Collaboration: Frequent updates and feedback loops ensure the infrastructure matches your exact expectations. 4️⃣ Deliver Impact: The final systems are intuitive, automated, and built for executive-level clarity. Would love to schedule a short call to discuss how we can architect the data infrastructure that fits your business needs.

I am a seasoned Data Engineer and Big Data Specialist with over 7 years of experience in building and optimizing scalable data pipelines, crafting real-time analytics solutions, and leveraging cloud technologies to deliver business value. My expertise spans across Big Data Ecosystems, Cloud Platforms, and Data Warehousing, ensuring end-to-end solutions for data-driven decision-making. 𝗗𝗼𝗺𝗮𝗶𝗻 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 : 𝗣𝗵𝗮𝗿𝗺𝗮𝗰𝗲𝘂𝘁𝗶𝗰𝗮𝗹 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 – Extensive experience in clinical data management, working with IQVIA, Sanofi, and optimizing study data pipelines for pharmaceutical research and trials. 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗦𝗲𝗰𝘁𝗼𝗿 – Expertise in the insurance domain, handling claims processing, policy data management, and ensuring compliance with industry regulations. 𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗺𝗲𝗻𝘁 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 – Worked with job advertisement data, company insights, geographical talent search, and salary analytics to enhance recruitment strategies. 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: Extensive experience in Big Data Analytics, specializing in Apache Spark, Kafka, NIFI, and Databricks, with a strong focus on Delta Lake, Streaming, and Batch Processing. Proficient in building robust ETL/ELT pipelines and designing OLAP data models using technologies Redshift, Snowflake, and BigQuery with dbt transformation. Hands-on expertise in AWS (Glue, S3, EMR, Lambda, Step Functions) and Azure (Databricks, ADF, CosmosDB) to build scalable, cloud-native architectures. Experienced in Docker containerization and deploying distributed applications across various environments. Adept at orchestrating data pipelines with Apache Airflow, Jenkins, and automated CI/CD workflows to streamline production deployments. Skilled in programming with Python and Pandas, with exposure to Scala for efficient data transformation and processing. 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩 & 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Proven track record in mentoring and leading technical teams, ensuring high-quality deliverables and fostering innovation. Experienced in collaborating with cross-functional teams, translating complex requirements into scalable solutions, and ensuring alignment with business goals. Passionate about adopting Agile (Scrum) and DevOps methodologies to enhance development efficiency and team collaboration. 𝐖𝐡𝐲 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐖𝐢𝐭𝐡 𝐌𝐞? I thrive on solving complex data challenges, driving impactful insights. Whether it’s optimizing data architectures, building real-time analytics solutions, or mentoring teams, Let’s connect and discuss how we can shape the future of data together!

[Updated on 01/07/2026] I assist businesses to create dependable, automatic pipelines and dashboards that they can believe. If your team is spending time on poor reports, manual data retrieval or decisions without data, you are not alone. I build all of the system from data ingestion through data transformation, to data warehousing and to reporting. You will have a data pipeline that operates independently and a dashboard that provides you with a clear view of what is going on in your business. Here's what that looks like in practice: • Fintex: Built a multi agent AI research platform for the Pakistan Stock Exchange. Uses Google Gemini for reasoning, FinGPT for financial analysis, Qdrant vector search over 10,000+ document chunks, Supabase PostgreSQL for real time stock OHLCV data, and SerpAPI for live news. Runs parallel data harvesting threads, scores confidence on every response, and renders interactive Recharts dashboards. Full stack: FastAPI, React, Docker, Nginx. • AnalyticsVisualAI: Designed an Agent to Agent platform where Claude orchestrates dashboard layouts and Gemini validates data quality and writes narrative reports. Users upload a CSV, type a question in plain English, and get a fully interactive dashboard with 9+ chart types, drag and drop grid layout, multi file joins, PDF export, and public share links. Built with Next.js, FastAPI, and Recharts. • Uber Trip Analytics: End to end pipeline using Apache Airflow for orchestration, dbt for SQL transformations, and Snowflake as the cloud warehouse. Raw trip data modeled into dimensional schemas that power executive dashboards in Power BI. • US Earthquake Monitoring: Real time ETL pipeline pulling from the USGS API, transforming and validating data in Python with automated quality checks, loading into Dockerized PostgreSQL, and delivering an interactive Power BI dashboard for seismic risk analysis. • Berlin Bike Theft Analytics: Raw police data into dbt dimensional models into Airflow orchestration with Cosmos into Snowflake into Power BI with city level drill downs and actionable crime insights. • Loan Portfolio Risk Dashboard: Complete data engineering pipeline using Airflow, PostgreSQL, Snowflake, and dbt to ingest, process, and transform loan and borrower data. Final output is a Power BI dashboard with borrower risk scoring and KPI tracking. • Olympics Data Pipeline: End to end pipeline taking Tokyo Olympics datasets from raw CSVs into PostgreSQL into dbt models into Power BI dashboard, fully containerized with Docker. • HR Analytics Pipeline: End to end HR data analytics pipeline covering ETL, cloud warehousing, and interactive dashboarding for workforce insights including attrition, compensation, and departmental KPIs. • Airflow PostgreSQL Power BI Pipeline: Complete ETL pipeline using Apache Airflow for scheduling and orchestration, PostgreSQL for storage, and Power BI for dashboard creation and visualization. • Crypto Currency Forecasting: Streamlit application for cryptocurrency time series forecasting using ARIMA and SARIMA models. Users upload CSV files, analyze price trends, check stationarity, and generate future price predictions with visual charts. • Mental Health Chatbot: Fine tuned Mistral 7B Instruct using QLoRA 4 bit quantization on 80,000+ empathetic dialogue pairs. Includes crisis keyword safety detection and a Gradio chat interface. Runs on consumer GPUs with gradient accumulation. • DevOps CI/CD Pipeline: Python application with Dockerfile, GitHub Actions CI/CD workflows, and monitoring infrastructure. Demonstrates containerized deployment and automated testing. Certifications: - SnowPro Associate Platform Certification from Snowflake. - dbt Fundamentals from dbt Labs - Databricks Fundamentals from Databricks - Dremio Verified Data Analyst from Dremio - dlt Fundamentals from dltHub What I work with: Pipelines and Orchestration: Apache Airflow, dbt, Mage, PySpark, Apache Kafka, Apache Flink Cloud and Warehouses: Snowflake, BigQuery, ClickHouse, AWS S3, AWS Glue, Athena, Lambda, Kinesis, GCS Databases: PostgreSQL, Supabase, Databricks, Dremio Visualization: Power BI, DAX, Looker Studio, Tableau Languages: Python, SQL Infrastructure: Docker, FastAPI I respond within a few hours. Send me a message with a quick summary of your data challenge, even if it's just "my reports are broken," and I will tell you exactly how I would approach it.

I am a data engineer/data analyst specialist working in the data field, working on many projects in financial tech and marketing analytics reporting. PROFILE - experience in ETL, BI, and Data warehousing. - Hands-on experience in Data VisuliaztionTools like Tableau and Looker - Experience in Data pipelines using Airflow. - Working knowledge of complete Data warehouse development life cycle (Data Modeling, Data warehouse designing, ETL development, BI reporting) - Exposure to large data volumes in major database systems including MySQL and PostgreSQL. -working with cloud services like S3 and Redshift - Experience in dbt tool

🚀 AI Engineer | LLM Specialist | Conversational AI | Machine Learning | Data Science | MLOps (AWS | Azure | GCP) 🤖📊 Hi, I’m Vishesh — an AI Engineer and Machine Learning Architect specializing in building LLM-powered applications, Conversational AI systems, and scalable ML platforms. I design and deploy end-to-end AI solutions that combine Generative AI, Data Science, and robust data engineering to solve real-world business problems. 💡 What I Do I help startups and enterprises build production-grade AI systems — from LLM-powered chatbots and AI agents to predictive ML models and data pipelines. Design LLM applications (chatbots, copilots, RAG systems, AI agents) Build end-to-end ML pipelines from data ingestion to deployment Develop scalable AI architectures with strong MLOps foundations Turn raw data into intelligent, automated decision systems 🧠 AI Engineering, LLMs & Conversational AI Build LLM-powered applications using LangChain, LangGraph, OpenAI, Hugging Face Transformers Develop Conversational AI systems (chatbots, voicebots, Q&A systems, virtual assistants) Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases Fine-tune and optimize LLMs (GPT, BERT, LLaMA) for domain-specific use cases Work with prompt engineering, embeddings, semantic search, and agent frameworks Build multi-agent AI systems and workflow automation using LangGraph Develop NLP solutions: sentiment analysis, summarization, entity recognition, classification 🤖 Machine Learning & Data Science Build ML models using XGBoost, Scikit-learn, TensorFlow, PyTorch Expertise in forecasting, anomaly detection, recommendation systems, and classification Apply statistical modeling, A/B testing, and causal inference Work with structured + unstructured data (text, logs, time series) 🛠️ Data Engineering & AI Pipelines Design scalable pipelines using Airflow, dbt, Spark, Kafka, Dask Build data lakes & warehouses (Snowflake, BigQuery, Redshift, Delta Lake) Enable real-time and batch data processing for ML systems Create clean, reliable datasets for training, inference, and analytics ☁️ MLOps, Deployment & Scalable AI Systems Deploy AI/ML systems using AWS SageMaker, Azure ML, GCP Vertex AI Build APIs & AI services using FastAPI, Docker, Kubernetes Implement CI/CD pipelines, model versioning, monitoring (MLflow, W&B) Design scalable, production-ready AI infrastructure 📊 Analytics & Business Intelligence Advanced analytics using Python, SQL, Pandas, Polars, Spark Build dashboards in Power BI, Tableau, Plotly, AWS Quicksight Deliver insights via forecasting, segmentation, experimentation, anomaly detection ✅ Why Clients Choose Me ✔️ Strong expertise in LLMs, Generative AI, and Conversational AI ✔️ Proven experience building end-to-end AI systems (data → model → deployment) ✔️ Deep understanding of MLOps & scalable AI architecture ✔️ Clear communicator who translates business problems into AI solutions ✔️ Experience across FinTech, SaaS, Logistics, eCommerce, Healthcare 🧰 Tech Stack Languages: Python, SQL, C++, Bash AI/LLMs: OpenAI, LangChain, LangGraph, Hugging Face, Transformers, RAG, Vector DBs ML/DL: PyTorch, TensorFlow, Scikit-learn, XGBoost Data Engineering: Airflow, dbt, Spark, Kafka, Dask Databases: PostgreSQL, MongoDB, Snowflake, BigQuery, Delta Lake Visualization: Power BI, Tableau, Plotly, Matplotlib, Seaborn MLOps: MLflow, Docker, Kubernetes, Terraform, FastAPI Cloud: AWS, Azure, GCP 📩 Let’s Build AI That Works If you're looking to build LLM-powered apps, AI agents, Conversational AI systems, or scalable ML pipelines, let’s connect. I can help you go from idea → prototype → production-ready AI system.

As a seasoned Data Engineer with 8 years of rich experience in crafting scalable data solutions, I excel in transforming complex data challenges into streamlined, efficient systems that drive business growth. With a Master's degree in Data Engineering, I bring deep expertise in data architecture, pipeline construction, and automation, underpinned by a robust proficiency in programming languages like Python and SQL, alongside mastery in big data frameworks and cloud platforms (AWS, Azure, GCP). My career highlights include leading strategic data migrations, developing cutting-edge analytics systems, and pioneering advanced ETL processes that significantly enhance operational efficiency and decision-making capabilities. At the heart of my approach is a commitment to leveraging technology to solve complex problems, and collaborating closely with cross-functional teams to foster a data-centric culture within organizations. I'm here to offer my extensive skills in data processing and analytics, database management, data visualization, and DevOps practices to empower your business with data-driven insights and solutions. Let's harness the power of your data to unlock new opportunities and propel your business forward.

As an experienced data engineer with over five years of experience, I specialize in designing and implementing scalable data solutions. I am proficient in ETL development, data warehousing, and data modeling. My skills include optimizing data pipelines, ensuring data quality, and supporting business decision-making with efficient data engineering practices. ​I have developed and maintained scalable ETL pipelines using Airbyte and dbt to support data warehousing and analytics workflows. I have also automated data ingestion from various sources into AWS-based data lakes and warehouses, ensuring high availability and accuracy. I am experienced in orchestrating workflows using Apache Airflow to enable timely and reliable data transformations and reporting. I can write optimized SQL and Python scripts for complex data modeling, transformation, and validation tasks. I have experience collaborating with data analysts, data scientists, and business stakeholders to define requirements and deliver high-impact data solutions. ​My expertise includes building high-performance ETL pipelines for machine learning workflows using Python, DuckDB, and Apache Airflow. I have also developed machine learning-ready data pipelines and normalized ERP datasets. Furthermore, I have designed scalable ETL workflows and dashboards using Alibaba Cloud. I have a strong background in improving operational efficiency through data solutions and handling ad hoc data requests. ​I am certified as a Databricks Data Engineer Associate. My technical skills include Python and Java programming; Big Data and Cloud technologies such as Apache Spark, Google BigQuery, and AWS; ETL tools like Talend Open Studio; and databases including MongoDB and SQL. I am also proficient in orchestration tools like Apache Airflow and Prefect.

With over 4+ years of experience, I have worked with top-tier brands such as Cosco Wholesale, FPT, Airbus, delivering scalable, secure, and high-performance solutions. I specialize in data engineering, analytics, AI/ML, and LLM-powered solutions, focusing on building robust ETL pipelines, optimizing data workflows, and ensuring seamless data integration across platforms. My expertise spans cloud-native, serverless, and microservices architectures. For LLM I have deep expertise in LangChain/LangGraph, Prompt Engineering, ChatGPT APIs, GPT Models, RAGs, Vector Databases and AI orchestration frameworks. I have extensive hands-on experience in data engineering, working with tools like Apache Airflow, Talend, AWS Glue, dbt, and Spark for ETL and large-scale data processing. I have designed and optimized data lakes and warehouses on GCP, AWS and Azure, leveraging PostgreSQL, MySQL, MongoDB, and Cassandra for structured and unstructured data. My expertise includes real-time data streaming with Pub/Sub, Apache Kafka and Kinesis, ensuring high availability and performance. I also specialize in AI/ML-driven data automation, leveraging LLMs for intelligent processing. My visualization expertise spans Looker Studio, Power BI, Tableau, and Grafana, enabling the creation of insightful, data-driven dashboards. With strong DevOps knowledge, including CI/CD, Docker, Terraform, and cloud infrastructure automation, I ensure scalable and optimized deployments. I am ready to start immediately and happy to discuss how my expertise can support your project.

Hi, Greetings! My name is Janardhan Reddy. *22+ years of experience in data platforms and data driven solutions of IT Consulting experience earlier worked with Global companies within the framework of industry best practices for fortune clients like Hewlett-Packard, Unilever, Cummins, SAP India, Dole, Capita, Legend, PepsiCo, Tesco, Yahoo, Nike, BNP Paribas, HDFC, PLA, Takada, PWC, KPMG,BT, McKinsey, MC Group, SHFL, Pernod Ricard etc • 20+ years of experience in architecting and implementation of large-scale data modeling, DW, EDW, ETL, ELT, MDM, CDP (Customer Data Platform), Big Data, data lake, delta lake, data catalog, data governance, data quality, Cloud-based data warehouse, OLTP and OLAP analytics platforms • 18+ years of experience in Data Visualization, Data Scientist. BI stakeholders and engineers to understand data, information, analytics, and business intelligence requirements • 15+ Defining the data architecture framework, standards, and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data, developing, technical documentation, data diagrams and data dictionaries • 10+ API / Integration Architect, Integration (API Platforms, CI/CD, ETL, DevOps), Big Data, Hadoop eco-system, Cloud Apps (AWS, Azure, GCP), Kafka, Spark • 10+ Enterprise Architect experience define and develop a comprehensive architecture, ensuring alignment with business goals and objectives, as well as industry best practices. • 6+ years of experience in Event-Driven Architecture(EDA): Event Streaming, Microservices, Messaging Service, ActiveMQ, RabbitMQ, JMS, CQRS & Event Sourcing • 6+ years of experience in Statistics & Probability for Data Science in Detail Sampling, Distributions, Normal Distribution, Descriptive Statistics, • 6+ Deep understand and experience algorithms Machine Learning, Deep Learning and NLP Models Assessment, Linear Regressions, Logistic Regressions, Decision Trees, Random Forests, KNN, SVMs, Neural Nets, CNNs, RNNs • 20 years of experience in implementation and strategizing enterprise and customer data platforms architecture for automotive, healthcare, CPG, retail , energy , e-commerce, pharma, FMCG, enterprise customers. Experience Tools and Technologies • Cloud Data Warehouse: Azure Synapse, Redshift, Google Big Query, Snowflake, Databricks, Vertica, Teradata, Oracle, IBM, Clickhouse • Data Science Tools: Python Deep dive into NumPy, Pandas, Matplotlib, Seaborn, Scikit Learn, Keras. SciPy, SymPy • Data Governance Tools: SAP MDM, Collibra, Informatica, Atlan, Alation, Oracle MDM, IBM MDM • CDP Tools: Segment, Amplitude, Blue shift, SAP, Oracle, Salesforce CDP, MS 365 insights • AI Models: Machine Learning, Deep Learning, NLP, Computer Vision, Tensorflow, Databricks • Api & Integration Tools: Workato, Informatica, Mule, Dell Boomi, Apigee, WSO2, Spring, SaaS Apps, • DevOps: Docker, Jankins, Kubernete, Confulant Kafka, MLOps, Jenkins Docker, AWS, Azure, GCP, Splunk, Grafana,Prometheus, Terraform " Analytics(BI): SAP BO, IBM Cognos BI, Oracle BI, Microsoft BI, Power BI, Pentaho, Tableau, QlikView, PowerApps, • Big Data Tools: Hadoop, Python, Spark, Pyspark, Scala, Kafka, Map Reduce, Pig, Hive, SAS, DBT, Airflow • EPM Tools: SAP BPC, IBM Cognos TM1, Oracle Hyperion, CXO Cockpit, CFO 4.0, Balanced Scorecard • Automation Tools(RPA): UiPath, Automation Anywhere, Blue Prism, • HRMS & CRM Tools: Oracle Cloud HCM, SAP Success Factors, Workday, MS CRM, SalesForce, • ERP Tools: SFDC(Salesforce), SAP R3 / SAP Hana, Oracle EBS, Oracle Cloud, Microsoft Dynamics

I am a Data Engineer with 3.5+ years of experience designing and delivering scalable data pipelines, data warehouses, and automated ETL/ELT solutions. I specialize in building reliable, production-grade data systems using Snowflake, DBT, Apache Airflow, AWS, Python, and SQL. My experience includes end-to-end data architecture design, data modeling, API integrations, workflow orchestration, and performance optimization. I have successfully built large-scale pipelines such as: • Real estate incentive and payroll data workflows using Snowflake + DBT + Airflow • End-to-end MLS data ingestion system integrating 800+ sources • Automated data transformation and validation pipelines • Column-level lineage and metadata validation systems for governance and impact analysis Beyond development, I lead and mentor a team of 9 engineers and collaborate with US-based clients to translate complex business requirements into efficient, scalable technical solutions. I am also a SnowPro Core Certified professional, committed to best practices in cloud data architecture, performance tuning, and data reliability. If you are looking for a Data Engineer who can: • Design scalable data pipelines • Build or optimize Snowflake data warehouses • Develop DBT models and transformations • Automate workflows with Airflow • Improve query performance and data quality • Deliver clean, production-ready solutions I would be glad to collaborate and add value to your project. Let’s connect and discuss your requirements.