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Data Engineer specializing in Python ETL pipelines for cloud data warehouses. I build automated data engineering solutions processing millions of records daily, from real-time trading data to healthcare analytics. With over 6 years of experience, I have developed production ETL systems on GCP and AWS using Apache Airflow, Dagster, and modern data stacks. I architect data engineering solutions that handle schema changes, ensure data quality, scale with demand, and prevent 3 AM pipeline emergencies. DATA ENGINEERING & ETL EXPERTISE ETL Pipeline Development & Data Engineering I design scalable ETL pipelines and data engineering infrastructure using Python with Apache Airflow or Dagster. My solutions include automated error handling, data validation, and comprehensive monitoring. Cloud Data Engineering (GCP & AWS) I build cloud-native data engineering solutions and ETL pipelines on modern platforms: GCP: BigQuery, Dataflow, Cloud Functions, Pub/Sub AWS: Redshift, Glue, Lambda, S3, Kinesis Enterprise Data Warehouse Migration Reduced ETL processing time by 60% moving to GCP. Python Data Engineering & Pipeline Orchestration Python expert for data engineering and ETL development. I implement robust data workflow orchestration using Apache Airflow and Dagster with pipeline monitoring for data quality and reliability KEY DATA ENGINEERING & ETL PROJECTS - Election Data Pipeline: Python + Dagster + Clickhouse solution extracting campaign finance data, automating 40 hours/week of manual processing. - Real-Time Trading Pipeline: Multi-layer architecture for algorithmic trading, achieving <100ms latency and 100% uptime. - Healthcare Data Migration: Led enterprise ETL migration to GCP BigQuery, resulting in 60% faster processing and 50% better performance. - ML Feature Engineering: Built end-to-end data pipeline for AirAsia's recommendation system, processing millions of records and increasing engagement by 25%. - Web Scraping ETL: Automated solution combining scraping with warehousing using Python and Apache Airflow. - AWS Cloud System Stabilization: Enhanced stability and performance of AWS-based systems, focusing on S3, Lambda, and webhook integrations. - Manufacturing Data Platform Expansion: Supported and expanded a manufacturing data platform with SQL Server, Azure SQL, and ERP data mappings. DATA ENGINEERING TECH STACK ETL & Orchestration: Apache Airflow, Dagster, Apache Spark, Kafka, dbt Languages: Python (Expert), SQL (Expert) Cloud Platforms: GCP (BigQuery, Dataflow), AWS (Redshift, Glue, Lambda) Databases: PostgreSQL, Clickhouse, MongoDB, BigQuery, Redshift, Snowflake Python Libraries: Pandas, PySpark, SQLAlchemy, Apache Beam Infrastructure: Terraform, Docker, Kubernetes, CI/CD IDEAL PROJECTS ETL pipeline development from scratch (Python, Airflow, cloud platforms) Data warehouse engineering and cloud migration (BigQuery, Redshift, Snowflake) Real-time data engineering and streaming ETL implementation Legacy ETL modernization and data pipeline migration Web scraping data engineering with ETL workflows Data integration connecting multiple sources ML data pipeline engineering for feature engineering LET'S BUILD YOUR DATA ENGINEERING SOLUTION Available for fixed-price data engineering projects and long-term ETL contracts. I work across US, European, and Asian time zones (GMT+7). Ready to discuss your data engineering and ETL needs? Send me a message. I respond within 2 hours during business hours.

Expert-Vetted AI & Full-Stack Engineer | 100% Job Success | 30+ Projects | $170K+ Earned Past Experience : Goldman Sachs, Morgan Stanley, KPMG, Oracle & Others I help startups and enterprises ship AI products and the backend systems behind them — from RAG chatbots and LLM integrations to scalable APIs, data pipelines, and production deployments. 10+ years building software. 30+ Upwork projects, all 5-star rated. Expert-Vetted (top 1%). One engineer who can own the problem from architecture to live product — clear communication, on-time delivery, code that scales. WHAT I BUILD AI & LLM • RAG chatbots and knowledge assistants over PDFs, docs, wikis, Notion, and internal APIs • LLM integration with OpenAI (GPT-4o, GPT-4), Anthropic Claude, and Google Gemini • AI agents with tool use — CRM, email, Slack, webhooks — plus guardrails and human approval • Streaming chat UIs with conversation memory, citations, and admin dashboards • LangChain, LlamaIndex, vector search (Pinecone, pgvector, Chroma, Weaviate, Qdrant) Backend & APIs • REST and GraphQL APIs in Python (FastAPI, Django, Flask), Node.js, and Java/Spring Boot • Microservices, event-driven architecture, authentication, and third-party integrations • PostgreSQL, Redis, MongoDB — schema design, optimization, migrations • Data pipelines with Kafka, Spark, and Airflow for analytics and ETL Frontend & Cloud • React, TypeScript, Next.js, Angular — SaaS dashboards and polished product UIs • AWS, GCP, Azure — Docker, CI/CD, monitoring, production hardening WHY CLIENTS HIRE ME Most AI projects break at the seams — weak APIs, messy data ingestion, no real UI, nothing deployed. I deliver the full path: data in → embeddings & retrieval → LLM → API → frontend → cloud.

🏆 TOP RATED PLUS Data Expert | Top 3% on Upwork 💰 $600K+ earned | 16,000+ hours | 130+ clients served I am a Sr Data Engineer with expertise in developing robust AI Agents & Analytics layer. I bring over 8 years of hands-on experience with: - Building scalable ETL data pipelines that fetch raw data froms APIs and store it into data warehouses hosted over GCP/AWS (BigQuery | Snowflake | Redshift). - Developing Business Intelligence reports and dashboards using Data Studio (formerly Looker Studio), Metabase, Looker, Tableau etc. - Building powerful AI Agents using Gemini, Claude, OpenAI, Dialogflow. - Track user behaviour data using GA4 and Google Tag Manager. I’ve worked with 130+ clients across eCommerce (Shopify, WooCommerce), digital marketing & paid ads (Meta, Google Ads), mobile apps & gaming analytics, SaaS & web apps, and data-driven businesses in education, clean energy & media. 💡 What I do (End-to-End Ownership) 1. Data Engineering & Warehousing: - Build scalable, reliable data pipelines using BigQuery, Snowflake, Redshift, Python and APIs of data sources - Automated ETL (Airflow, APIs, Fivetran, custom Python scripts) - Single source of truth across marketing + product + revenue 2. Analytics & BI (Decision Systems, not just dashboards): - Executive dashboards (Looker, Data Studio (formerly Looker Studio), Metabase, Power BI, Tableau) - KPI frameworks aligned to revenue - Cohort, LTV, attribution & funnel analysis 3. Marketing & Web Tracking (Accuracy = $$$) - GA4, Google Tag Manager, Server-side tracking - Meta CAPI, Google Ads, TikTok tracking - Fix broken attribution & data loss 4. Generative AI & Automation - AI agents & workflows (OpenAI, Gemini, Claude) - Automate reporting, insights, and ops - Use AI where it actually improves ROI (not hype) 📈 Real Outcomes I’ve Delivered ✔ Built full marketing data warehouse → improved spend efficiency by 30%+ ✔ Fixed tracking & attribution → recovered lost revenue visibility ✔ Automated reporting → saved 20+ hrs/week for teams ✔ Delivered exec dashboards → faster, data-backed decisions 🧠 Why Clients Choose Me - I think like a business owner, not just an engineer - I focus on revenue impact, not vanity metrics - I handle end-to-end (tracking → pipelines → dashboards → insights) - Strong communication + fast execution (no hand-holding needed) 📈 My Tech Stack: - Business Intelligence & Data Visualisation: Google Data Studio (formerly Looker Studio) , Looker, Metabase, Power BI, Mode, Tableau, Databox, Zoho Analytics, DOMO, Google Sheets, etc. - AI: LLMs like OpenAI, ChatGPT, Gemini, Claude, DeepSeek, and GCP's services like Document AI, DialogFlow, CCAI, etc. - Engineering: SQL, Python, Airflow, APIs, Cloud Functions, Lambda Functions, Cloud Composer, Cloud Run - Data Warehouses: BigQuery, Redshift, MS SQL, MySQL, PostgreSQL, Snowflake, and Azure. - ETL & Webhook tools: n8n, Fivetran, Stitch, Windsor, Supermetrics, Power My Analytics, Saras Analytics, Zapier, Make, etc. - Tracking: Google Tag Manager, Google Analytics 4, Meta Ads Conversion API, Google Ads Conversion tracking, Stape, Server-side tracking. - Data Sources: Shopify, WooCommerce, BigCommerce, Meta Ads, Google Ads, TikTok Ads, Pinterest Ads, LinkedIn Ads, Apple Ads, Amazon Ads, Bing Ads, Google Analytics 4, Google Search Console, Google My Business, HubSpot, Active Campaign, PipeDrive, Facebook Page Insights, Instagram Insights, Stripe, SEMRush, MailChimp, Klaviyo, ClickUp, Ahref, etc. 👉 Let’s Work If you’re looking for someone who can own your entire data stack and turn it into a revenue engine, let’s talk. Click “Invite” and let’s discuss your use case 🚀 ----- 🔍 𝗞𝗘𝗬𝗪𝗢𝗥𝗗𝗦 GA4, Google Analytics 4, Google Tag Manager (GTM), Server-side Tracking, Meta Conversion API (CAPI), Google Ads Conversion Tracking, Marketing Attribution, BigQuery, Snowflake, Redshift, Data Warehouse, Big Data, Data Engineering, ETL, ELT, Data Pipelines, Apache Airflow, Airflow DAGs, PySpark, Spark, Databricks, SQL, Python, Advanced SQL, Data Modeling, Data Transformation, Data Architecture, Data Lakes, Data Studio, Looker Studio, Power BI, Tableau, Data Visualization, Dashboard Development, Business Intelligence (BI), KPI Dashboard, Reporting Automation, Shopify Analytics, WooCommerce Analytics, Marketing Analytics, Product Analytics, Funnel Analysis, Cohort Analysis, LTV Analysis, Retention Analysis, Generative AI, OpenAI, ChatGPT, Gemini, Claude, AI Agents, AI Automation, AI Agents, LLM Applications, n8n, Workflow Automation, No-code Automation, Low-code Automation, Zapier, Make (Integromat), API Integrations, Webhooks, Stripe, HubSpot, Google Ads, Meta Ads, TikTok Ads, LinkedIn Ads, Cloud Platforms (GCP, AWS), Cloud Functions, AWS Lambda, Data Orchestration

I Engineer self-healing, AI augmented data automation systems that eliminate manual workflows and scale seamlessly. By combining advanced Python backend architectures (FastAPI, Django) with Azure AI and OpenAI, I build intelligent pipelines that don't just move data they autonomously extract, classify, validate, and enrich it. One system. Runs infinitely. Zero manual intervention. PROVEN IMPACT & CASE STUDIES Enterprise Document Automation: Engineered an automated tax-compliance pipeline leveraging Azure AI Document Intelligence and Python, completely replacing 100% of manual tax form processing with a single-click AI verification system. Mission-Critical Architectures: Designed and deployed a secure, end-to-end digital examination and data management platform for NASTP (National Aerospace Science & Technology Park), eliminating intensive manual administrative workflows. E-Commerce Data Warehouse & Custom API Pipeline: Architected a robust, scalable multi-source data extraction pipeline utilizing advanced ETL methodologies to ingest, clean, and sync high-volume market data into performance-optimized databases. CORE SPECIALTIES & HOW I DELIVER VALUE AI-Augmented ETL/ELT Pipelines Building resilient ingestion frameworks that use LLMs (OpenAI GPT-4o, Azure OpenAI) to process unstructured documents, PDFs, and raw text. Python structures the incoming data, Pydantic v2 strictly validates it, and PostgreSQL stores it securely. Custom API Architectures & Data Warehousing Developing high-performance, asynchronous REST APIs using FastAPI and Django. I integrate complex third-party webhooks, handle rate-limiting seamlessly, and model scalable relational databases backed by SQLAlchemy, Alembic migrations, and advanced SQL (CTEs, Window Functions). Serverless Cloud Deployment Deploying production-grade pipelines onto AWS (S3, Lambda, RDS) and Azure Blob Storage. Your systems run on fully automated schedules in the cloud without requiring manual infrastructure management. Enterprise BI & Analytics Dashboards Transforming raw, automated data warehouses into interactive, executive-level insights using Microsoft Power BI and custom Streamlit web applications. TECH STACK AI & Intelligence: OpenAI API · Azure AI Document Intelligence · Prompt Engineering Backend & APIs: Python · FastAPI · Django · Uvicorn · REST APIs · Pydantic v2 · Docker Data Automation & ETL: Pandas · NumPy · Custom Ingestion Pipelines · SQL Databases & ORM: PostgreSQL · SQLite · SQLAlchemy · Alembic · Snowflake Cloud Infrastructure: AWS (S3, Lambda, RDS) · Azure Cloud Storage BI & Analytics: Microsoft Power BI · Streamlit. Need data automated, AI-enhanced, or securely piped? Click "Invite to Job" to schedule a technical discovery call. I respond to all inquiries within 4 hours.

I build custom data and AI solutions that fit your business. Not off-the-shelf tools that sort of work. Hands-on, direct communication, full accountability. Projects of any size. A lead-scoring model for Salesforce. Large-scale ETL with Snowflake, Airflow, and Python. Custom analytics applications that answer questions your team actually asks. When projects need more capacity, I tap a trusted network of developers and analysts I've worked with for years. What I build: - AI integrations (RAG, agents, document intelligence, local LLMs) - Data infrastructure (Snowflake, Airflow, dbt, Python) - Custom analytics applications - Cloud architecture (AWS, Azure, GCP) 8+ years. 100% Job Success. Top Rated Plus. Expert Vetted. If you want solutions built for how your business actually works, let's talk.

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. 🎯 Core Expertise: ✅ Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. ✅ Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. ✅ Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. ✅ Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!