Hi, I'm a Professional Data Engineer specializing in robust data pipelines, analytics solutions, and automation systems. I transform complex data challenges into scalable, production-ready solutions that drive business value. ⭐⭐⭐⭐⭐ Core Specializations • Data Pipeline Development • ETL/ELT Process Design • Analytics & Visualization • Web Scraping & Automation • Data Warehouse Architecture • Full-Stack Web Development • API Development & Integration • AI/ML Integration ➡️ Complete Technology Stack: ✅ Modern Data Stack: dbt • Airflow • ELT Pipelines • Data Quality Testing • Data Modeling ✅ Analytics & Visualization: Tableau • Custom KPIs • Interactive Visualizations • Streamlit Applications ✅ Data Processing & Storage: Python (Pandas, NumPy) • SQL (MySQL, PostgreSQL, BigQuery) • Data Warehouse Design • Big Data Processing ✅ Full-Stack Development: Next.js • Vanilla JavaScript • Bootstrap/CSS • HTML5 • Django • FastAPI • REST APIs ✅ AI/ML Integration: LangChain • OpenAI APIs • Custom AI Tools • ML Model Integration • Intelligent Automation • AI-Powered Data Processing ✅ Automation & Extraction: Web Scraping (BeautifulSoup, Selenium) • ETL Automation • Custom Python Scripts • API Development ✅ DevOps & Tools: Git • CI/CD Pipelines • Docker • Testing & Documentation • Agile Methodologies 🚀 What Sets Me Apart: • End-to-end solutions from data ingestion to AI-powered dashboards • Scalable data pipelines with modern stack tools • Interactive web applications with AI integration • RESTful APIs connecting data services to frontend applications • Automated data quality checks and monitoring systems • Complete ETL/ELT solutions with real-time processing • AI/ML automation tools leveraging LangChain and OpenAI 📊 Proven Track Record: • Automated data pipelines processing millions of records daily • AI-powered analytics applications with LangChain integration • Interactive Tableau dashboards and Streamlit applications • Full-stack web applications with Django/Next.js • Custom APIs handling thousands of requests per minute • Comprehensive web scraping solutions with AI enhancement • Robust data quality frameworks with intelligent monitoring 🎯 Project Approach: Clean, maintainable code • Scalable solutions • Modern practices • Clear communication • Meeting deadlines • Continuous optimization 🏆 Why Choose Me: • Dual Expertise: Data engineering + full-stack development + AI/ML • Modern Tech Stack: Latest tools and frameworks including AI integration • End-to-End Solutions: Database to AI-powered user interfaces • Quality Focus: Clean code, testing, documentation • Business Value: Solutions driving real outcomes • Immediate Availability: Ready to start and deliver results Ready to transform your data challenges into AI-powered opportunities! Let's connect and discuss how I can drive your data initiatives forward. Warm regards, Suryansh

I am a Senior Data Engineer & AI Specialist with 7+ years of experience designing and building scalable data pipelines, modern data warehouses, analytics platforms, and AI-powered data solutions. I specialize in ETL/ELT pipeline development, data modeling, business intelligence, and integrating AI/LLM-based workflows into data systems. My core expertise includes SQL, Python, Data Engineering, ETL/ELT pipelines, data architecture, and cloud-based analytics solutions. I have hands-on experience working with PostgreSQL, MySQL, Amazon Redshift, ClickHouse, and modern data stack tools such as Airflow, dbt, and AWS (S3, Lambda, Glue, Redshift). I design and optimize high-performance data pipelines for batch and real-time processing, ensuring data quality, consistency, and scalability. I build robust data models (star schema, snowflake schema), data marts, and centralized data warehouses to support business intelligence and analytics use cases. I also develop dashboards and reporting solutions using Power BI and Tableau, enabling data-driven decision-making through actionable insights, KPI tracking, and advanced SQL-based analytics. In the AI space, I build and integrate LLM-powered solutions, including Retrieval-Augmented Generation (RAG), AI automation workflows, and data-driven AI applications using OpenAI APIs and Python frameworks. I have experience building intelligent data pipelines that combine analytics with machine learning and AI capabilities. Additionally, I have experience in product analytics, A/B testing, experimentation frameworks, and applying machine learning models for predictive analytics and data-driven optimization. I am highly focused on performance optimization, data quality, scalability, and delivering reliable, production-grade data systems. I work effectively in agile environments and collaborate with cross-functional teams to turn data into business value.

I am a skilled BI Developer and Data Engineer with 8 years of experience in data analysis and value extraction. My work focuses on designing and orchestrating modern data pipelines, transforming data into actionable insights for businesses. I specialize in Power BI, SQL, and have advanced in data engineering with recent training in MLOps, covering tools like Airflow, dbt, and platforms such as Snowflake and Databricks. My approach blends hands-on industrial experience with modern data architecture practices, enabling me to create reliable data models and efficient workflows. If you need a data expert who can elevate your analytics capabilities and drive informed decision-making, let’s discuss how I can contribute to your project.

Data engineer with 6+ years building reliable, scalable data pipelines that turn raw, messy data into systems businesses can actually trust and run on. I specialize in designing and automating ETL/ELT pipelines, modeling data warehouses, and optimizing data infrastructure so teams stop firefighting broken reports and start making decisions with confidence. My work spans the full data lifecycle — from ingestion and orchestration to transformation, testing, and documentation — using tools like [SQL, Python, Airflow, dbt, Snowflake/BigQuery — swap in her actual stack]. [Achievement/metric goes here — e.g. "Rebuilt a client's reporting pipeline, cutting manual processing time by 70% and eliminating recurring data errors."] I care about clean, well-documented systems over quick hacks — pipelines that the next person (or future me) can actually understand and maintain. I work closely with analytics and product teams to make sure the data answers the real business question, not just the technical one. If you need someone who can take a data mess and turn it into a dependable, automated system — let's talk about your project. I look forward to applying my problem-solving skills and technical expertise, enabling businesses to make data-driven decisions. I'm a person who is highly oriented, meticulous, and hard-working to ensure the user's problems are solved, scaling up products and improving all aspects of it. I also work closely with the product team to strategize and execute the development of data products. And Conduct mentorship sessions for software developer aspirants. Passionate about leveraging my skills and experience to contribute to dynamic organizations and drive meaningful results. Thank you for visiting my profile!! Open to all friendly suggestions and opportunities to connect professionally.

Data & AI Engineer | BI Dashboards, ETL Pipelines & Cloud Data Solutions I help businesses transform raw, scattered data into reliable data pipelines, clean data models, and actionable dashboards that support faster, smarter decision-making. With 3+ years of hands-on experience across enterprise and industrial environments, including projects with Continental, Mercedes-Benz, and other business clients, I specialize in building end-to-end data solutions that are scalable, maintainable, and business-focused. My core expertise includes: * BI & Dashboarding: Power BI, Tableau, and Excel dashboards, interactive reporting, data model optimization, DAX performance tuning, and star/snowflake schema design for scalable analytics. * ETL/ELT & Data Engineering: Designing, building, and orchestrating pipelines using Python, SQL, Airflow, dbt, and Apache Spark. I integrate data from SAP, Redshift, SharePoint, APIs, SQL databases, and other sources into clean, business-ready data layers. * Cloud Data Platforms: Azure Databricks, Azure Data Factory, Log Analytics, Azure DevOps, AWS S3, Redshift, EC2, and DynamoDB for scalable storage, processing, deployment, and monitoring. * Monitoring & Observability: Grafana, ELK Stack, Elasticsearch, Logstash, Kibana, and KQL-based dashboards for pipeline health, system performance, error tracking, and operational visibility. * AI & Machine Learning: Applying AI/ML techniques to real-world data and signal-processing use cases, including model evaluation, deployment, and practical business implementation. * Automation: Python and Excel VBA automation for recurring reports, manual workflow reduction, improved accuracy, and faster delivery. I am comfortable owning a project from start to finish: understanding business requirements, designing the data architecture, building pipelines, modeling data, and delivering polished dashboards that stakeholders can actually use. Whether you need a one-time dashboard, an ETL pipeline rebuild, cloud data migration, data automation, or ongoing BI support, I bring a structured, detail-oriented approach with clear communication throughout the project. Let’s discuss your data challenges and turn them into reliable, decision-ready insights.

Data Engineer with 3+ years of experience designing, building, and maintaining scalable data pipelines and lakehouse architectures in production environments. Experienced in developing end-to-end ETL and data processing workflows using PySpark, SQL, Databricks, Airflow, and Delta Lake, with a strong focus on reliability, performance optimization, and maintainability. Core expertise includes: • Distributed data processing with PySpark and Apache Spark • ETL pipeline development and workflow orchestration • Delta Lake, Unity Catalog, and data governance • Data modeling, schema evolution, and incremental processing • Data quality validation, testing, and pipeline reliability • Performance optimization and production support Platforms & Technologies: • Databricks • AWS (S3) • Apache Spark, Airflow • Delta Lake, Unity Catalog • dbt, Snowflake • Git, CI/CD workflows In addition to production data engineering experience, I’ve built independent projects using modern analytics and AI stacks, including dbt, Snowflake, GCP, and retrieval-augmented generation (RAG) systems. I enjoy building clean, scalable, and well-documented data systems that support analytics, BI, and downstream data applications.

🚀Hi! I help startups go from demo → market-ready AI product - fast! I plug into your team and ship production ready features that customers love. 🏆 Top 1% (Expert-vetted) | 8+ years| 100% JSS | 35+ Delighted Clients | 18+ E2E Deployments 🎯 "𝘒𝘶𝘯𝘫𝘢𝘯 𝘪𝘴 𝘢𝘯 𝘢𝘣𝘴𝘰𝘭𝘶𝘵𝘦 𝘨𝘦𝘮! 𝘚𝘩𝘦 𝘸𝘦𝘯𝘵 𝘢𝘣𝘰𝘷𝘦 𝘢𝘯𝘥 𝘣𝘦𝘺𝘰𝘯𝘥. 𝘛𝘦𝘢𝘮𝘪𝘯𝘨 𝘶𝘱 𝘸𝘪𝘵𝘩 𝘩𝘦𝘳, 𝘸𝘦 𝘣𝘶𝘪𝘭𝘵 𝘳𝘰𝘣𝘶𝘴𝘵 𝘥𝘢𝘵𝘢 𝘱𝘪𝘱𝘦𝘭𝘪𝘯𝘦𝘴, 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘦𝘥 𝘓𝘓𝘔𝘖𝘱𝘴, 𝘵𝘳𝘢𝘯𝘴𝘪𝘵𝘪𝘰𝘯𝘦𝘥 𝘧𝘳𝘰𝘮 𝘧𝘢𝘯𝘤𝘺 𝘥𝘦𝘮𝘰𝘴 𝘵𝘰 𝘢 𝘴𝘤𝘢𝘭𝘢𝘣𝘭𝘦 𝘈𝘐 𝘱𝘳𝘰𝘥𝘶𝘤𝘵 𝘵𝘩𝘢𝘵 1000𝘴 𝘰𝘧 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘭𝘰𝘷𝘦!" - CTO, Healthcare startup, SF (1 of many 5-star reviews) Over 7+ years on Upwork, I've helped startups and enterprises across sectors - Marketing, Healthcare, Law, Education, and Agribusiness - translate AI into measurable business ROI by building the right data and ML foundations. Whether collaborating with 1000+ employee companies or lean 2-person startups, I adapt to the team’s needs: reporting directly to CEOs or CTOs as an AI/Data Lead, or integrating as a hands-on contributor alongside in-house developers. I bring a “brain-for-hire” + hands-on mindset - tackling strategic and technical challenges with equal enthusiasm, always focused on delivering outcomes, not overhead. 👀 See 8+ Case Studies & Demos: totemxlabs dot com/#casestudies 🎯 Recent Success Stories (2024-2025) 1. Graph RAG for Marketing & Strategic decisions Implemented knowledge graph-powered RAG systems using Neo4j for marketing intelligence and SEO optimization - enabling sophisticated knowledge checks and relationship-based insights that traditional RAG cannot achieve. 2. Workplace Safety Vision System Deployed end-to-end computer vision solution for workplace health and safety compliance - real-time hazard detection, PPE verification, and automated incident reporting. 3. Healthcare Diagnostic Knowledge Graph Developed evidence-based diagnostic system using knowledge graphs for healthcare - producing auditable, traceable diagnostic reasoning paths that meet clinical documentation standards. 🧭 My Proven AI Product Process: Discovery: Identify high-ROI AI opportunities aligned with your goals. Data Assessment: Evaluate data availability, relevance, quality. Solution Design: Define user journeys, tech stacks, evaluation frameworks. Development: Optimized sprints for cost-effective, robust AI solutions (min. tech debt). Deployment: Scalable architectures, rigorous testing for production readiness. 💡 Technical Expertise: GenAI & LLMs: LLM Ops (Fine-tuning, Prompt Engineering, RAG, Agentic Workflow, Multi-agent systems, Memory Management), LangChain, LangGraph, LlamaIndex, LangServe; Vector Search (Pinecone, Weaviate, Chroma, FAISS). AI/ML & MLOps: Predictive Analytics, Recommender Systems, RLHF; Model Lifecycle, MLflow, Feature Stores; PyTorch, TensorFlow, Scikit-learn. Cloud & Infra (Multi-cloud): AWS (Lambda, ECS, ElastiCache, DynamoDB, API Gateway), Azure, GCP, Vertex AI, SageMaker; Docker, Kubernetes (EKS/GKE). Software & Data Eng: Python (expert), Fullstack; FastAPI, Flask, Django; REST, GraphQL, OpenAPI, AsyncIO; Batch/Stream (Airflow, Spark, Kafka), Pandas, Polars, dbt; ETL/ELT. DBs/Arch/DevOps: PostgreSQL, MySQL, DynamoDB, MongoDB, Vector DBs (Pinecone, Weaviate, ChromaDB), Neo4j; Microservices, GitHub Actions, Terraform, CI/CD pipelines. 🤝 Why Partner With Me? I help architect and develop E2E AI solutions merging tech excellence with business acumen. Let's transform the AI wave into your competitive edge. ✅DM me if you have an exciting problem to solve! —Updated January, 2026— Latest LLMs (2025-26): GPT-5.2 (OpenAI's flagship with 26% lower hallucination rate) Claude 4.5 Opus & Sonnet 4.5 (200K context, breakthrough coding performance) Gemini 3 Pro & Flash (Deep Think mode, multimodal excellence, 1M token context) DeepSeek V3.2 & R1 series (685B parameters, hybrid thinking/non-thinking modes) Qwen 3 series (open weight dense and mixture-of-experts (MoE) model for reasoning tasks) Agentic AI Frameworks: Langchain & LangGraph (stateful graph-based workflows, production-grade orchestration) OpenAI Agents SDK (lightweight with guardrails and handoffs) CrewAI (role-based multi-agent collaboration, human-in-the-loop) LlamaIndex Agents (RAG-first agent capabilities) AI workflow automation: n8n Knowledge Graphs & Graph RAG: Neo4j 2025 features: Community summaries, parallel retrievers, LLM Knowledge Graph Builder Neo4j Aura Graph Analytics Graph RAG architecture Cypher query optimization, graph embeddings for ML Agentic knowledge graph construction with provenance Computer Vision Applications: Workplace safety, Video generation Multimodal Vision Language Models (VLMs) Context engineering for high quality content generation

Drowning in data but starving for insights? Pipelines breaking while dashboards show stale numbers? I fix both sides of that problem — I build the infrastructure AND deliver the analysis. Most freelancers are either a data engineer who can't tell a business story, or a data analyst who can't handle scale. I'm both. With 12+ years across Fortune 500 companies, I build the pipelines that move your data AND create the dashboards, reports, and analyses that turn it into decisions. AT A FORTUNE 500 FMCG COMPANY, I: → Reduced BigQuery processing costs by 95% — saving $XXk/year → Improved query execution speed by 15–120x through materialized views and smart optimization → Built consumer analytics pipelines processing millions of records across 3+ international markets → Designed KPI frameworks and automated reporting that replaced 40+ hours/month of manual work → Created consumer segmentation models driving targeted marketing across multiple channels DATA ENGINEERING — I BUILD IT: - End-to-end data pipelines (ingestion → transformation → serving) - Cloud data warehouse design and optimization (BigQuery, Snowflake, Databricks) - Modern data stack implementation (dbt, Delta Lake, Airflow, Terraform) - Data quality frameworks, deduplication, and cross-system reconciliation - AI-ready infrastructure — RAG pipelines, feature stores, LLM integration DATA ANALYSIS — I MAKE IT USEFUL: - Interactive dashboards and executive reporting (Looker, Data Studio, Tableau, Power BI) - KPI design and automated business metrics tracking - Customer segmentation, cohort analysis, and behavioral analytics - Ad-hoc deep dives — churn analysis, funnel optimization, revenue attribution - GA4 analytics, UTM attribution modeling, and marketing performance analysis TECH STACK: SQL · Python · BigQuery · Snowflake · Apache Spark/PySpark · dbt · GCP (Cloud Functions, Pub/Sub, Dataflow, Composer) · Databricks · Delta Lake · Airflow · Terraform · Docker · Looker · Tableau · Power BI · GA4 · Pandas · scikit-learn · Git BACKGROUND: 12+ years across Fortune 500 companies in retail, technology, consulting, and CPG. I've worked at the intersection of engineering and analytics my entire career — building systems at scale while staying close enough to the business to know what actually matters in the data. I work in your timezone when needed, communicate clearly, and document everything so your team can maintain what I build. Available for hourly consulting, fixed-price projects, and ongoing retainers. Let's talk about what your data should be doing for you.

I build production-grade data & AI systems that turn messy sources into reliable, decision-ready outputs. From marketing mix modeling to Bayesian A/B testing and LLM products, I have shipped many working products. What I Deliver: ✅ Warehouses & pipelines (BigQuery/Postgres) with clean schemas, tests, monitoring ✅ Marketing analytics: unite all sources to create dashboards that inform ✅ Experimentation: Bayesian A/B framework, uplift analysis, forecasting ✅ LLM services: FastAPI endpoints for RAG/structured outputs, evals, cost controls Stack I Use: → Python, SQL, AWS, Postgres, Power BI, Streamlit → FastAPI, LLMs, Modal, Airflow, Jenkins, Git, Docker Why makes me different: → Not just product building - clear communication. Proven experience dealing with customers. → Operator mindset: ship quickly, validate impact, automate the boring parts → Strong grasp of growth metrics (LTV, CAC, MER, retention) and experiment design

I help companies design, build, and modernize scalable data platforms that turn raw data into reliable analytics, automation, and AI-ready products. I’m a Senior Data Engineer / Cloud Data Engineer with 9+ years of experience building production-grade data pipelines, lakehouse platforms, ETL/ELT systems, cloud data warehouses, real-time streaming pipelines, and analytics-ready data models across AWS, Azure, GCP, Databricks, Snowflake, Redshift, BigQuery, SQL Server, and modern AI/GenAI workflows. My strongest work is in: • Cloud Data Engineering: AWS Glue, Lambda, S3, Redshift, Athena, EMR, Step Functions, Azure Databricks, ADLS, ADF, Synapse, GCP BigQuery, Dataflow, Pub/Sub • Databricks & Lakehouse: PySpark, Delta Lake, Unity Catalog, Medallion Architecture, Bronze/Silver/Gold pipelines, performance tuning, partitioning, Z-Ordering • ETL / ELT Pipeline Development: Python, SQL, PySpark, dbt, Airflow, Dagster, Spark, Kafka, APIs, batch and near-real-time ingestion • Data Warehouse Modernization: SQL Server, SSIS, Oracle, legacy ETL migration to Databricks, Snowflake, Redshift, and BigQuery • Data Modeling & Analytics: dimensional modeling, star schema, fact/dimension tables, semantic layers, Power BI, Tableau, Domo, QuickSight • Data Quality & Governance: data validation, reconciliation, monitoring, lineage, metadata, access control, CI/CD, automated testing, and production support • GenAI / AI Data Platforms: RAG pipelines, vector search, embeddings, LangChain, LangGraph, LLM workflows, AI-ready datasets, and enterprise knowledge platforms I specialize in solving messy, real-world data problems: broken pipelines, slow SQL, unreliable dashboards, disconnected systems, manual reporting, poor data quality, and cloud migration challenges. I can take a project from requirements gathering to architecture, development, testing, deployment, documentation, and long-term support. What clients can expect from me: • Clean, maintainable, production-ready code • Strong communication and clear project ownership • Scalable cloud architecture designed for performance and cost efficiency • Reliable pipelines with monitoring, error handling, and documentation • Business-focused delivery, not just technical implementation • Fast ramp-up on existing systems, data models, and business logic I have worked across banking, aviation, energy, SaaS, analytics, and enterprise data platform environments, supporting teams with data migrations, reporting modernization, cloud warehouse builds, Databricks lakehouse development, Domo to Redshift migration, SQL Server to Databricks migration, real-time streaming pipelines, and AI/ML data infrastructure. If you need a data engineer who can own the work end-to-end, communicate clearly, and deliver reliable systems that your business can trust, I’d be happy to help.