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Hi, I’m Mohsin a Senior Data Engineer and Cloud Engineer helping businesses build reliable data systems, automate workflows, and turn raw information into useful business insights. I specialize in designing and developing scalable data pipelines, cloud data platforms, analytics systems, and AI-powered solutions using modern tools across AWS, GCP, and Azure. I can help you with: Data Engineering & Pipelines Building ETL/ELT pipelines, data lakes, data warehouses, and real-time data workflows using Python, SQL, Spark, Airflow, Kafka, dbt, and cloud-native services. Cloud Data Platforms Designing secure and cost-efficient data architectures on AWS, GCP, and Azure using services like S3, Glue, Redshift, BigQuery, Dataflow, Synapse, Databricks, and Snowflake. AI, ML & Automation Creating practical AI/ML workflows, automation systems, predictive models, and cloud-based ML deployments using tools like SageMaker, Vertex AI, Azure ML, MLflow, and Python. DevOps & Deployment Setting up CI/CD pipelines, Docker, Kubernetes, Terraform, GitHub Actions, monitoring, and production-ready deployment workflows. My focus is not just writing code. I help businesses create systems that are stable, scalable, easy to maintain, and useful for real decision-making. I can support you with: ✅ Data pipeline development ✅ Cloud migration and architecture ✅ Data warehouse and lakehouse setup ✅ Dashboard-ready analytics models ✅ Workflow automation ✅ AI/ML model deployment ✅ Performance optimization ✅ Data quality and reliability improvements I believe in clear communication, clean engineering, and delivering solutions that actually solve business problems. If you need someone who can take ownership from planning to deployment, I’d be happy to help.

🔝 𝐓𝐨𝐩-𝐑𝐚𝐭𝐞𝐝 𝐅𝐫𝐞𝐞𝐥𝐚𝐧𝐜𝐞𝐫 𝐨𝐧 𝐔𝐩𝐰𝐨𝐫𝐤 🚀 𝗦𝘁𝗿𝘂𝗴𝗴𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝘀𝗹𝗼𝘄 𝗱𝗮𝘁𝗮 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗼𝗿 𝘂𝗻𝗿𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗘𝗧𝗟 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀? 𝗜 𝗯𝘂𝗶𝗹𝗱 𝗮𝗻𝗱 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗵𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗱𝗮𝘁𝗮 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝘁𝘂𝗿𝗻 𝗺𝗮𝘀𝘀𝗶𝘃𝗲 𝗱𝗮𝘁𝗮𝘀𝗲𝘁𝘀 𝗶𝗻𝘁𝗼 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀. With 4+ years of professional experience, I have worked as a Data Engineer at world-class tech giants Xiaomi (Fortune Global 500) and Shopee ($80B Market Cap). My expertise lies in transforming complex data challenges into seamless, efficient, and scalable data workflows. ⭐ How I Can Elevate Your Business: ✔ End-to-End ETL/ELT Pipeline Development: I architect and build fully automated data pipelines using Airflow and Apache Spark (Scala/Python/Java), ensuring timely and accurate data for your analytics and machine learning models. ✔ Spark Performance Tuning & Optimization: Is your Spark job running slow or failing? I specialize in deep-diving into Spark applications to diagnose bottlenecks, optimize resource utilization (memory/CPU), and significantly cut down processing time and cost. ✔ Big Data Architecture & Solutions: Leveraging modern data stack tools like Kafka, Flink, Hadoop (HDFS, Hive), and Druid, I design and implement scalable Data Lakes and Data Warehouses tailored to your specific business needs. ✔ Data Quality & Integrity: I implement rigorous data cleaning and validation processes, transforming raw, messy data into a pristine, reliable asset for your decision-making. ⭐ Core Technical Skills: ✔ Big Data Ecosystem: Apache Spark, Airflow, Kafka, Flink, Hadoop, Hive, HDFS, Druid ✔ Programming: Scala, Python, Java, SQL ✔ Databases: HBase, Redis (NoSQL), Relational SQL Databases ✔ Platforms: Data Lake, Data Warehouse, AWS, GCP ⭐ What Sets Me Apart: ✅ Problem-Solver, Not Just a Coder: I focus on understanding your business goals first, then architect a solution that delivers real value. My work at Xiaomi was praised for not just meeting, but exceeding expectations by foreseeing future needs. ✅ Proactive & Clear Communication: You will always be in the loop. I believe in transparent, frequent updates to ensure the project aligns perfectly with your vision. ✅ Partnership & Kindness: I see my clients as partners. I am committed to working collaboratively and kindly to make your project a success and your life easier. Ready to build a data infrastructure that drives your business forward? 𝗝𝗨𝗦𝗧 𝗖𝗟𝗜𝗖𝗞 𝗢𝗡 𝗜𝗡𝗩𝗜𝗧𝗘 𝗕𝗨𝗧𝗧𝗢𝗡 and let's have a quick chat about your project goals.

I am a senior software developer and architect (Total- 21 Yrs.) in Java/J2ee, Python, Rest API, SOAP API, javascript, OAuth, SSO, React, Redux, Angular, Kafka, SpringBoot, JPA, Cloud, AWS, Azure, Private cloud, JBPM, n8n, Oracle BPM, JMS, Hibernate, Struts, Spring Batch, ESB, Base44, Playwright, Selenium, JavaFX, Lisp, Prolog, Weka , OpenAI, Different Web as well as Application Servers, different Operating Systems and DBMS Tools, SQL, NoSQL, PostgreSQL, Mongo, Cassandra, MYSQL, Oracle, Supabase, AI, NLP, OpenAI, agent development, Wordpress, php , CI/CD, Agile and various open-source tools, technologies and frameworks. Some of the domains I have worked on are Banking, finance, Trade, Crypto, HR, Insurance, Learning, NLP, Healthcare, System architecture, Developers Tooling, Document management, AI, DevOps, Cloud, GCP, Hubspot, Quickbook, PandaDoc, Stripe, etc. ********************************************************************* Experience Summary: Freelancing || Freelancing || Present Toyow || Solution Architect || Sep 24 to JAN 25 JPMorgan || Vice President || (Around 12 Yrs. Total) Deloitte || Senior Consultant/Specialist Senior || Jun 13 to Jun 15 HCL || Onsite/Offshore Dev lead || Sep 06 to May 10 Birla Soft Ltd || Software Engineer || Jan 06 to Sept 06 GIIT || Developer || Feb 05 to Oct 05 ************************************************************************* Some of the applications are as below which I have developed/contributed. - Document generation system - Online translation system using NLP - Library management system - HRMS System - Networking system - Tools for Developer and Operate to build and deploy their applications. - Workflow as a service - Workflow Platform for Mutual Fund NAV processing (Fund accounting) - Prediction analysis for SLA miss. - A real time dashboard for fund processing - Messaging Platform supporting MQ, SFTP, REST, Kafka, FIX, - Trade instruction manager - Customer support system for Bank operators - Platform for Tokenization Assets using Blockchain - A social Media application - A insurance management Platform - Applications developed on Base44 - Loan record reports - OCR for healthcare reports and data processing. - ChatBot for Patient enquiry. - Coin analysis using AI (openAPI integration). - A Platform for affiliate marketing. - CI/CD for Gitlab and AWS.

I'm Huanqing Zhu, and you can call me Fusion. With over 10 years of hands-on Java development experience—including 6 years dedicated to big data processing and visualization—I’ve built my expertise by staying rooted in frontline coding, even as my responsibilities have grown. A key pillar of my technical toolkit is ‌6 years of production-grade Rust development experience‌, complemented by proficiency in Java, Scala, JavaScript, HTML5, and a full stack of big data and cloud-native technologies: Apache Spark, Hadoop, Hive, Flume, HBase, Storm, Kafka, DataX, ECharts, Docker, Kubernetes, and Linux. What sets me apart is that I’ve never stepped away from writing production code, even as I’ve taken on leadership and architectural roles: As a ‌hands-on Big Data Developer‌, I’ve built robust data ingestion utilities (including the open-source DataXServer on GitHub) and real-time page click analytics systems, directly coding pipelines to pull data from RDBMS, NoSQL databases, and file storage into production environments. As a ‌Big Data Architect‌, I’ve led platform design while still contributing core code, using Hadoop, Spark, Flink, and ElasticSearch to build scalable data infrastructure—no abstract planning here; I’ve written the critical components that power these systems. As a ‌Rust Specialist‌, my 6 years of experience spans building high-performance, low-latency systems. I’ve used Rust to optimize data processing pipelines, cut latency by up to 40% in high-throughput scenarios, and deliver systems that run 24/7 with zero critical errors. As a ‌Team Leader‌, I’ve managed full-stack teams (Java, front-end, QA, operations) while still pairing with developers on complex code reviews and contributing to high-priority features, ensuring I stay connected to the day-to-day challenges of software delivery. I also bring deep experience in microservices architecture and cloud-native containerization, and my cross-language expertise lets me bridge gaps between Java-based enterprise systems and Rust-powered high-performance components. If you’re looking for a professional who combines strategic vision with the grit to deliver production-ready code—someone who can architect a system, and write the Rust or Java code that makes it run—I’m the candidate for you. Thank you for reviewing my profile. I’m eager to discuss how my hands-on experience can add value to your team.

I build reliable, production-grade data pipelines on AWS for teams that need accurate data, predictable costs, and systems that scale without breaking. I’m an AWS data engineer with 6 years of experience designing and running ETL/ELT pipelines, data lakes, and analytics platforms used for decision-making and compliance. If your pipelines fail silently, dashboards can’t be trusted, or costs keep rising, the issue is usually the architecture — not the tools. I work with: S3, Glue, Lambda, Step Functions Redshift, Athena, Snowflake (AWS) Kinesis, MSK / Kafka Airflow What you get: Clean, well-documented data models Monitored pipelines (no silent failures) Cost-efficient, scalable AWS designs Systems your team can operate without me If you’re struggling with broken pipelines, slow analytics, or rising AWS data costs, message me. I’ll tell you quickly if I can help and what I’d do first.

🏆 TOP RATED PLUS || Top 1% on Upwork || 8+ Years of Experience || 100% Job Success || Expert Vetted Most data teams are held back by unreliable pipelines, untrustworthy warehouses, and data infrastructure never built to scale. That's exactly what I fix. As a Senior Data Engineer, I don't just write SQL and call it a pipeline. I architect end-to-end data systems where reliable ingestion feeds into clean, versioned transformations that power decisions your business can act on. My approach prioritizes fault tolerance, scalability, and observability across both batch processing and real-time analytics workloads. This ensures your data infrastructure is not just functional, but resilient and audit-ready. Whether you need cloud data migration, data platform modernization to a Modern Data Stack (Snowflake/dbt/Airflow, Microsoft Fabric), or streaming analytics infrastructure, I deliver production-grade systems that help technical founders and data teams eliminate pipeline debt, automate complex data workflows, and build scalable infrastructure ready for AI workloads. ------------------------ Where I make the biggest impact: ✅ I lead data migration and data platform modernization projects, replacing brittle ETL and ELT pipelines with a Modern Data Stack built on Snowflake, dbt, Airflow, and Microsoft Fabric. ✅ Every engagement includes Medallion Architecture design, full test coverage, CI/CD for data models, data lineage tracking, and documentation that outlasts the project. ✅ I design data pipelines for both batch processing and real-time analytics, idempotent, schema-drift tolerant, and monitored through data observability frameworks, so failures are caught before they reach your stakeholders. ✅ Warehouse models are built to serve the business: Star Schema, dimensional modeling, dbt projects, analytics engineering best practices, and a metrics layer backed by a data catalog and metadata management. ✅ I architect distributed systems for big data and streaming analytics, including Kafka, Flink, Spark Structured Streaming, exactly-once semantics, dead-letter queues, and end-to-end latency guarantees. ✅ AI data pipelines are engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ✅ I bring governance to data platforms through data mesh, data catalog implementation, metadata management, and data integration across systems. ✅ Data quality and data reliability are enforced end to end, with automated frameworks, SLA monitoring, auditable lineage, and observability that catches bad data before it reaches your stakeholders. ✅ I build AI-ready data infrastructure and lakehouse foundations, Delta Lake, Apache Iceberg, cloud data architecture, and CDC pipelines for near-real-time sync. ✅ Cloud data migration is handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime. ------------------------ What I Build With: 🗄️ Warehouses, Lakehouses & Data Lakes: Snowflake, BigQuery, Redshift, Databricks, Microsoft Fabric, Delta Lake, Iceberg ⚙️ Transformation: dbt (Core & Cloud), SQLMesh, Spark, PySpark, Star Schema, Medallion Architecture 🔁 Orchestration: Airflow, Dagster, Prefect, Azure Data Factory, Microsoft Fabric 📨 Streaming: Kafka, Kinesis, Pub/Sub, Flink, Fabric Eventstream 🔗 Ingestion: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, CDC pipelines ☁️ Cloud: AWS, GCP, Azure 🐍 Languages: Python, SQL (SF, BQ, 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 ⭐ "Adarsh built our entire data platform from the ground up. Clean architecture, solid dbt models, and Airflow pipelines that have been 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 Adarsh with a Spark pipeline that was costing us a fortune and delivering stale data. He identified the bottlenecks, restructured the workflow logic, and reduced our processing time by 70%. Technically sharp, communicates clearly, and delivers without hand-holding." – Leo, Head of Analytics, HealthTech SaaS ------------------------ 🚀 Let's Build Your Data Foundation. If your data infrastructure needs to be faster, cleaner, and trustworthy, send a quick message about your project, and I'll take it from there.