Data Engineer building the full-stack intelligence layer for modern businesses. I architect, implement, and maintain the complete data-to-insights value chain. I deliver three interconnected pillars: Reliable Data Infrastructure: Scalable pipelines, cloud data warehouses, and ELT processes. Actionable Business Intelligence: Dashboards, reports, and self-service analytics that inform strategy. Intelligent Automation: Production AI/ML models, RAG systems, and LLM integrations that predict outcomes and automate complex tasks. With deep expertise across the modern data stack (AWS/Azure/GCP, Snowflake, Databricks, Kafka, Airflow, dbt, Power BI/Tableau, Python ML stack, RAG/LLMs), I ensure your data assets are operational, insightful, and intelligent.

I'm a fractional CTO for founders and teams who need senior technical leadership without a full-time hire — with two exits behind me. I spent 7 years as CTO at Perfsol, growing the technical org through to a successful sale in 2025. In parallel, I founded Upsky, an AI startup that went from founding to acquisition in under a year (2024–2025). That combination — long-term technical ownership at Perfsol and a fast AI-native build at Upsky — is what I bring to clients: the discipline to architect systems that last, and the speed to ship AI products before a market window closes. Recent freelance engagements back this up with hands-on range: ~2 years architecting and scaling the dev effort for a fintech startup (MXNEY), 2+ years owning DevOps infrastructure for a production system (Cura), an embedded full-time stint building a Vue.js application for an early-stage startup (Lenox.ai), and recent AI agent development (Lindy, Google OCR pipelines) for teams automating their operations. Also Top Rated Plus on Upwork, $417K+ earned across 100 completed projects, with earlier in-house roles as Solution Architect at EPAM Systems, Data Architect at Kyriba (fintech), and Data Warehouse Architect at Norsk Hydro. What I typically own: technical strategy and architecture decisions a non-technical founder can trust, AI/automation adoption (n8n, Make, Python, OpenAI/Claude/Azure OpenAI), data and cloud architecture (Azure, Snowflake, ETL), and DevOps/infrastructure oversight so a system stays reliable as it scales.

With 6+ years of experience as a Data Engineer & AI Specialist, I design ETL/ELT pipelines, AI-driven analytics, and scalable cloud solutions that transform raw data into intelligence. I work across AWS, GCP, Azure, and Snowflake to deliver data engineering, AI automation, and real-time analytics for industries like fintech, real estate, and SaaS. From AI-powered RAG pipelines to enterprise-scale data warehouses, I create solutions that are robust, cost-efficient, and production-ready. 🧠 Generative AI & Machine Learning LLMs: OpenAI (GPT-4o), Gemini, Claude, LLaMA, Hugging Face, LangChain, LlamaIndex RAG Pipelines & Vector Databases: Pinecone, FAISS, Weaviate AI Tools: Prompt Engineering, Fine-Tuning, Model Deployment, MLflow, TensorFlow, PyTorch NLP & Forecasting: Topic modeling, Churn prediction, Real-time analytics ⚙️ Data Engineering & Pipelines Orchestration & ELT: Airflow, DBT, Dagster, Prefect, Fivetran, Airbyte, Meltano, dlt ETL / Data Pipelines: Python, SQL, Spark, Dask, Pandas, NumPy Data Warehousing: Snowflake, BigQuery, Redshift, Databricks, Delta Lake, DuckDB APIs & Automation: FastAPI, Flask, REST APIs, Web Scraping, API Integrations Scraping & Data Extraction: Scrapy, Selenium, Playwright, BeautifulSoup, Cloudflare Bypass, Proxy Rotation 📊 Data Visualization & Analytics Tableau, Looker, Power BI, Google Data Studio, QuickSight, Plotly, Dash, Seaborn, Matplotlib Real-time dashboards & business intelligence for decision-making ☁️ Cloud & DevOps AWS: Lambda, Glue, Athena, S3, Redshift GCP: BigQuery, Dataflow, Cloud Run, Vertex AI Azure: Data Factory, AI Services, Synapse Docker, CI/CD, Serverless, Cloud-native AI 🛠 Workflow Automation n8n, Make (Integromat), Zapier, Airtable, No-Code Data Engineering 🎯 Keywords (for Upwork SEO) Python, SQL, Python, Apache Spark, PySpark, Snowflake, Spark, BigQuery, Redshift, Databricks, Databricks Platform, Spark, ETL, ELT, DBT, Airflow, Prefect, Dagster, Fivetran, Airbyte, Meltano, MLflow, Hugging Face, TensorFlow, PyTorch, LLM, RAG, LangChain, Vector Databases, Pinecone, Weaviate, FAISS, NLP, Forecasting, Scrapy, Selenium, BeautifulSoup, Playwright, API Development, Web Scraping, Data Warehousing, Data Engineering, Automation, n8n, Make, No-Code Pipelines, Cloud Data Engineering, Database, API Integration, Data Analysis, Data Science, Database Architecture, AI Agent Development, AI App Development 🔖 Hashtags #DataEngineering #ETL #ELT #AIEngineering #LLM #GenerativeAI #Snowflake #BigQuery #Databricks #ApacheAirflow #DBT #RAG #LangChain #VectorDB #PythonDeveloper #APIAutomation #WorkflowAutomation #n8n #Make #NoCodeDataEngineering #MachineLearning #CloudData #Database #APIIntegration #DataAnalysis, #DataScience #ApacheSpark #Spark #AIDataEngineering #WorkflowAutomation #Snowflake #BigQuery #ApacheAirflow #PythonDeveloper #NoCodeDataEngineering #n8n #Make #dbt #PySp #DatabaseArchitecture #DatabricksPlatform #AIAgentDevelopment #AIAppDevelopment

Extensive experience (16 years) in Oracle, MySQL, SQL Server, Postgres, Snowflake and Azure Data Lake methodically identifying and resolving complex underlying causes of problems, using a vast variety of techniques and tools. I have solved numerous show-stopping Performance problems, as well as often re-engineered immensely complex designs and code, providing significantly improved performance. Have designed data warehouse and implemented ETL pipeline strategies on AWS and Azure. Extensive experience as a Data Engineer with multiple work experience in data extraction, data transformation, data load, data protection, data cleansing, data migration, data mergers etc. Expert level ability with Data Architecture, Data Modelling and Data Analysis. I can conceptualize, design and develop long-term, automated, integrated solutions with a focus on increasing your competitive advantage. Have also held roles where I had to work with business end users to provide Solution Architecture and drive the solution from discussing with the users to delivering the final solution product to the end users. Have around 6 years of experience in Python (ETL and Data Analytics), 4 years in Tableau, 2.5 years in DBT and 2 years in Matillion (ETL). Domain expertise: Freights and Logistics (Quotation, Pricing, Booking, Reservation, Inventory management, Operations, Control products for Accenture Freights and Logistics Solutions) - 7 years Finance - Capital Market (Backend book-keeping for different instruments for BNP Paribas) - 3. years Digital Marketing (Generic product for Call Center and Website for a Digital Marketing company called Candid Maven) - 2 years Merchant Data Platform (Creating the automated framework from scratch to bring in data that was managed in Smartsheet to the centralized database using Python and PL/SQL to serve the analytic needs - for a company called Woflow that holds 96% of the market in this domain) - 6 months Pharmaceutical (Data Lake and Data Warehouse setup for Precision for Medicine - integrated systems like CRM (Saalesforce), ERP (Infor CloudSuite, PSA), HR (Greenhouse, ADP, PSA, SAP Success Factor), RM (Smartsheet, WorkFront), Clinical vendor data (Citeline, KMR) - 3 years At Precision for Medicine, I have worked on integrating the data of all the above mentioned disparate data platforms in 1 single dimension model (ERP, HR, RM, CRM) for creating the centralized enterprise analytics platform. I am eager to work with you, to provide reliable, consistent, and High-Level solutions to design/development challenges. Please contact me, so we can discuss how we can work together to FULLY meet your Business Needs!

You're probably generating more data than you know what to do with. Most of it sits in dashboards nobody opens, or feeds reports nobody trusts. I fix that. 25 years building data infrastructure for companies from startups to Fortune 500, across the US, Latin America, and Europe. On Upwork since 2016, Expert-Vetted (their top 1% of independent talent). I'm not an agency, and I don't do offshore handoffs. It's just me, doing the work you need done. And my work history can testify that I can get it done. I've been the fractional CTO reporting to CEOs at data-heavy companies, the data lead serving a C-suite, and the extra pair of senior hands inside an existing team. The structure can be flexible, but I'll never loose the standards. What I actually deliver: Reporting people trust. Not dashboards that look impressive in meetings, but numbers that trace back to source and survive hard questions. A recent client discovered they'd been overstating ARR for years. I rebuilt it from transaction data and now the figure holds up in due diligence. AI and ML that reaches production. I've shipped forecasting models, document extraction, and analytics agents that run daily in live businesses. One recent model beat the client's specialist analyst on 7 of 10 product categories. Where it lost, I told them why, because knowing the limits is part of the job. Audits that find real money. Pricing analysis for a SaaS client surfaced $193K a year in unintended cross-subsidies between customer tiers. A BI audit for a UK wholesaler found board reports that couldn't be traced to source, plus the path to fix them. Integrations that stop being fragile. QuickBooks, Unleashed, Salesforce, SAP, Chargebee, Snowflake, and the long tail of tools mid-market companies actually run. Stack: Python, R, SQL (PostgreSQL, MySQL, MS SQL), Snowflake, AWS, Azure. BI: Qlik Sense, Power BI, Tableau. AI/ML: Anthropic Claude, OpenAI, custom models. Plus GIS, forecasting, and marketing analytics when the problem calls for it. Tell me what's not working and I'll tell you honestly whether I'm the right person for it. Sometimes I'm not, and I'll say so. When I am, you'll know within one conversation.

I am an experienced Data Engineer with 5 years of hands-on experience in ETL, Data Engineering, Data Modeling, Data Integration, and Data Warehousing. My work mainly emphasizes reliability, efficiency, challenge, and simplicity. If you are looking for someone with a broad skill set who can work as a team member and take on the responsibilities of the tasks. I have experience and knowledge in the following areas, tools, and technologies: ►Data Storage: S3, Azure Storage, Google Cloud Storage ► Data Warehouse: Google BigQuery, Snowflake, Azure Synapse Analytics ► DATABASES: SQL Server, MySQL, PostgreSQL, MongoDB, Oracle, Google Cloud Big Table ►Data Lake: Azure Data Lake Storage, AWS Lake Formation ► Data Transformation, Data Integration, Data Governance, Data Quality: Azure Data Factory, Azure Synapse, Amazon Glue, Fivetran, DBT ► Monitoring Tools: Amazon Cloudwatch, New Relic, Dynatrace, Datadog ► BI, Visualization, Data Analyst: Power BI, Metabase, Sigma BI ► OTHER SKILLS & TOOLS: SQL, Python, Rest API ► I can also work on different technologies and tools if required

Lead specialist data engineering, data science, cloud, and AI team at Agility.AI Act as lead architect on every engagement — direct technical ownership, not delegated oversight Vetted delivery team executes behind the architecture; no large-consultancy overhead, no solo-generalist risk 100% Job Success Score | Top Rated 200+ data engineering projects | 200+ AI/ML implementations | 80+ cloud migrations delivered ⭐ DATA ENGINEERING Pipeline architecture, ELT, real-time streaming — Snowflake, Databricks, dbt, Apache Kafka, Apache Spark Warehouse/lakehouse design — Snowflake, BigQuery, Redshift, Synapse — 60-80% query runtime reduction ERP/CRM integration — SAP, Oracle, Dynamics, Salesforce — with master data management and full lineage 500TB+ processed daily | 99.9% uptime | 6-10 weeks kickoff to production ⭐ DATA SCIENCE & MACHINE LEARNING Predictive analytics — time-series forecasting, demand modeling, churn prediction (scikit-learn, XGBoost, custom neural networks) Deep learning, NLP (classification, entity extraction, sentiment analysis), computer vision (object detection, OCR, quality inspection) MLOps — model monitoring, automated retraining, drift detection (SageMaker, Azure ML, Vertex AI) 85% average model accuracy across 50+ production ML models | ROI within 8-12 weeks ⭐ CLOUD & INFRASTRUCTURE MIGRATION On-prem to cloud (AWS, Azure, GCP) and cloud-to-on-prem repatriation — same team, either direction Database, ETL, warehouse, storage, and application migration — zero data loss, phased cutover, parallel-run validation Terraform IaC, Kubernetes, CI/CD — reproducible, auditable environments 80+ migrations | zero data loss | 40-60% infrastructure cost reduction | 99.9% post-cutover uptime ⭐ AGENTIC AI & LLM SYSTEMS Production multi-agent systems — LangChain, LangGraph, CrewAI, AWS Bedrock RAG pipelines with hallucination prevention and enterprise compliance checkpoints 50K+ daily queries at sub-300ms latency — measured in production ⭐ ENTERPRISE BI & POWER PLATFORM Governed Power BI ecosystems — RLS, Fabric Lakehouse, DirectLake Board-level reporting accuracy standards ⭐ PROVEN RESULTS Manufacturing: 88% forecast accuracy | 40% safety stock reduction | SAP/Siemens MES/Oracle SCM integration Healthcare: 95%+ diagnostic ML accuracy | 85% cardiac risk prediction (30-day advance) | 78% incident reduction across 40+ EMR systems FMCG: Full on-prem to Azure migration | 200+ stored procedures | 1,000+ SSRS to Power BI | 40% cost reduction | zero data loss Insurance: 500+ daily statements automated | 95% manual entry reduction | 70% claims latency reduction Pharmaceuticals: 70% cost reduction | 100% pipeline automation | 15+ global clients Retail: 20% sales uplift | 25% stockout reduction ⭐ WHO WE WORK WITH Organizations with legacy infrastructure outgrowing its current platform — cloud-bound or repatriating Organizations with data fragmented across systems AI initiatives funded but stuck in prototype Migration, model, or compliance requirements needing an accountable architect, not just a spec-writer ⭐ NEXT STEP 30-minute scoping call Fast start once fit is confirmed

I'm a Senior Data Engineer with 4.5+ years of experience building scalable, cloud-native data platforms that turn raw data into reliable, business-ready insights. I've delivered enterprise solutions across banking (NAB), healthcare (Molina), and CPG (PepsiCo), specializing in end-to-end pipeline architecture, data modeling, and cloud migrations. What I bring to your project: 🔹 Cloud Data Engineering – Deep expertise in Azure (Databricks, Data Factory, Synapse) and AWS (EMR, Glue, S3, RedShift), with hands-on migration experience from on-prem and Teradata to cloud. 🔹 Pipeline Architecture & ETL – I design and build robust ingestion frameworks handling batch, incremental, and real-time data (Event Hub, Kafka) across formats like JSON, CSV, Parquet, and fixed-width files. 🔹 Data Modeling & Warehousing – Skilled in dimensional modeling, Data Vault, star/snowflake schemas, and silver/gold layer design. I've modeled 50+ tables across Oracle Fusion, SAP S/4, and healthcare domains. 🔹 Transformation & Orchestration – I translate complex business rules into DBT models, orchestrate workflows with Apache Airflow or AutoSys, and automate CI/CD via Jenkins and Azure DevOps. 🔹 Performance & Governance – I tune PostgreSQL and Spark jobs, implement data quality checks, reconciliation frameworks, and ensure compliance with data governance standards. 🔹 Generative AI & MLOps – Databricks-certified in Generative AI, with experience integrating MLflow for experiment tracking and building LLM-based automation using OpenAI and LangChain. Tech Stack: Python | SQL | Scala | Apache Spark | DBT | PostgreSQL | Snowflake | Airflow | Databricks | Azure | AWS | Git | Jenkins | MLflow | Power BI Certifications: Databricks Certified Data Engineer Professional | Azure Data Engineer (DP-203) | Snowflake SnowPro Core | Fabric Analytics Engineer (DP-600) | Generative AI Engineer Associate Whether you need a production-grade pipeline, a cloud migration, or a well-modeled data warehouse, I deliver clean, documented, and scalable solutions — on time and with clear communication. Let's discuss your project!

4+ years owning the full BI vertical, from raw source extraction to agentic AI layer. I don't cover parts of the stack. I run the entire system: ingestion, modeling, warehousing, visualization, deployment, and AI implementation. Zero handoff gaps. Zero "that's not my scope." 🧠 𝐖𝐡𝐚𝐭 𝐓𝐡𝐢𝐬 𝐌𝐞𝐚𝐧𝐬 𝐅𝐨𝐫 𝐘𝐨𝐮 🔹 Extraction & Pipelines: APIs, web scraping, file ingestion, Stripe, Shopify, Zoho, GA4, Ads platforms, pulled, validated, and landed in your warehouse. No manual CSV drops. No broken syncs. 🔹 Modeling & Architecture: Star schemas, SCDs, fact and dimension tables, marts, catalogs, grain reconciliation. A semantic layer built for Day 2, not just Day 1. 🔹 Visualization & Design: Power BI, Looker Studio, Zoho Analytics, Superset, DOMO, Metabase. UI/UX-informed dashboards with intentional hierarchy, color theory, branding alignment, and storytelling that makes the insight obvious, not buried. 🔹 Deployment & Governance: Row-level security, role management, access control, documentation. Production-grade, not prototype-grade. 🔹 AI Layer: Conversational analytics, self-serve ad-hoc queries, proactive strategic briefings, alert systems against goals and benchmarks, pipeline and validation (Red Cell) agents. AI as infrastructure, not as demo. ⚙️ 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗧𝗼𝗼𝗹𝗯𝗼𝘅 🔹 BI & Viz: Power BI, Looker Studio, Zoho Analytics, Metabase, Superset, Domo 🔹 Modeling & Query: SQL, DAX, Power Query (M), Python, dbt, Excel 🔹 Warehousing: BigQuery, Snowflake, Cloud SQL, Cloud Storage, SQL Server, MySQL, Postgress, SQL Server, Amazon Redshift, Amazon S3 🔹 Pipelines & ETL: Make, n8n, Fivetran, Apps Script, Cloud Run, Python, Supermetrics, Windsor AI, Coupler AI, Airbyte, JS 🔹 Cloud & Governance: Google Cloud Platform, AWS, Azure, Terraform, Git 🔹 AI: OpenAI & Claude APIs, agent orchestration, anomaly detection, predictive models, automated briefings & alerts 🚀 𝗧𝗵𝗲 𝗔𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 When you hire a data analyst, you get dashboards. When you hire a data engineer, you get pipelines. When you hire me, you get the system, no gaps between extraction and insight, no friction between layers, no risk of one contractor's output breaking another's input. 🔹 One point of accountability across every layer of the stack 🔹 Decisions in plain language for technical and non-technical stakeholders 🔹 Architecture built for growth, not just for the deliverable 💡 𝐋𝐞𝐭'𝐬 𝐁𝐮𝐢𝐥𝐝 𝐘𝐨𝐮𝐫 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦 Your business generates data. I make sure every byte of it moves, transforms, lands, and speaks, without friction, without gaps, and without you needing to manage the in-between. Not a dashboard. Not a pipeline. That's a decision system.

I am a Lead Data Scientist and Data Engineer with over 10 years of experience turning messy, complex datasets into scalable, high-accuracy predictive systems and automated data pipelines. I specialize in the Retail/FMCG and Healthcare/Pharmaceutical sectors, bridging the gap between advanced technical architecture and actionable business strategy. Backed by an Executive PG in Data Science & AI from IIT Roorkee and holding Microsoft Certifications in Python and Azure (AZ-900 & DP-100), I build the "intelligence layers" that drive enterprise decision-making. My Core Technical Expertise: Data Engineering & ETL: GCP (BigQuery), SQL, dbt, Parquet, Batch Processing, Multiprocessing Programming & AI/ML: Python (Pandas, Scikit-learn, Regex, Flask, Streamlit), R, SAS, Predictive Modeling, GenAI Business Intelligence & Viz: Power BI, Looker, Clinical Dashboards Proven Domain Impact: Retail & FMCG: Engineered automated POS data pipelines (36-month initiative), improving loading efficiency by 30%. Led a 24-month product harmonization project using predictive modeling to resolve discrepancies across millions of records. Designed GCP/BigQuery demand forecasting pipelines to optimize supply chain inventory. Healthcare & Clinical Analytics: Deep experience integrating open-source tools (Python, R, SAS) for clinical trial data visualization. Proficient in building interactive clinical dashboards utilizing Pharmaverse, SDTM, and ADaM datasets. Cloud Architecture & Metrics: Migrated massive datasets to modern cloud environments and developed robust DAU/MAU tracking structures inside BigQuery and Looker. Why Work With Me? I do not just execute code; I solve business problems. Alongside my technical career, I manage my own coworking space business, meaning I inherently understand the commercial urgency, stakeholder management, and extreme ownership required to deliver ROI. Whether you need to deploy an AI model, untangle enterprise ERP data, or build an interactive dashboard from scratch, I write clean, maintainable, and production-ready code. Let’s connect to discuss how we can scale your data infrastructure and build models that actually impact your bottom line.