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 — and increasingly the AI/RAG pipelines that sit on top of them. With 6+ years of experience, I design production ETL systems on GCP and AWS using Apache Airflow, Dagster, and modern data stacks: schema-change handling, data quality checks, and monitoring that means no more 3 AM pipeline pages. WHAT I DO ETL Pipeline Development I design scalable pipelines in Python with Airflow or Dagster — automated error handling, data validation, and monitoring built in from day one, not bolted on after the first outage. Cloud Data Engineering (GCP & AWS) GCP: BigQuery, Dataflow, Cloud Functions, Pub/Sub AWS: Redshift, Glue, Lambda, S3, Kinesis Data Warehouse Migration Migrated a legacy warehouse to GCP, cutting ETL processing time by 60%. AI/LLM Data Pipelines Retrieval-augmented generation (RAG) pipelines — document ingestion, chunking, vector search, and streaming LLM responses — for teams that need their data pipelines to feed an AI product, not just a dashboard. KEY PROJECTS - Election Data Pipeline — Python + Dagster + ClickHouse pipeline extracting campaign finance data, automating 40 hours/week of manual work. - Real-Time Trading Pipeline — Multi-layer architecture for algorithmic trading with <100ms latency and 100% uptime. - Healthcare Data Migration — Led an enterprise ETL migration to GCP BigQuery, cutting processing time by 60%. - ML Feature Engineering (AirAsia) — End-to-end pipeline feeding a recommendation system, processing millions of records and lifting engagement 25%. - AI Document Chat (RAG) — Built a local/cloud retrieval-augmented generation app (Python, ChromaDB, FastAPI/React) supporting both local (Ollama) and cloud (Anthropic, OpenAI) models, with streaming answers and live web-search augmentation. See portfolio. - Web Scraping ETL — Automated scraping-to-warehouse pipeline in Python and Airflow. - AWS Cloud Stabilization — Improved stability and performance of AWS systems: S3, Lambda, and webhook integrations. - Manufacturing Data Platform — Extended a manufacturing data platform across SQL Server, Azure SQL, and ERP data mappings. TECH STACK ETL & Orchestration: Apache Airflow, Dagster, Apache Spark, Kafka, dbt AI/LLM: RAG pipelines, vector databases (ChromaDB, Pinecone), OpenAI/Anthropic APIs Languages: Python (expert), SQL (expert) Cloud: GCP (BigQuery, Dataflow), AWS (Redshift, Glue, Lambda) Databases: PostgreSQL, ClickHouse, MongoDB, BigQuery, Redshift, Snowflake Python: Pandas, PySpark, SQLAlchemy, Apache Beam Infra: 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 / streaming data engineering - Legacy ETL modernization - RAG and AI data pipeline engineering - Data integration across multiple sources - ML feature-engineering pipelines Available for fixed-price projects and long-term contracts. I work across US, European, and Asian time zones (GMT+7) and respond within 2 hours during business hours.

I'm a software engineer experienced in building high-load services, websites for small and medium-sized businesses, for media companies who really care about latency and every milliseconds is matters. Have wide experience in building full systems from scratch, providing as the result deployment pipelines, well documented code, and well-tested highly covered, stable solutions. My main proficiency in delivering Node.js solutions for different type of projects, made with Nest.js as a primary framework, using different type of storages like Redis, DynamoDB, MySQL, ClickHouse, etc... I usually do full project management from start till the end of the project. I would really appreciate to solve your business needs and dive in to the problem statement to support your business vision

I'm a Data Engineer with 6 years of experience in building and managing data solutions across industries like telecom, cybersecurity, and e-commerce. I specialize in creating efficient data architectures that enhance business intelligence and operational efficiency. Key Skills - Data Warehousing: ClickHouse, Amazon Redshift - ETL Pipelines: Apache Airflow - Databases: MySQL, PostgreSQL, MongoDB, Cassandra - Cloud Platforms: AWS, Google Cloud - Programming: Python, Golang, Scala

I help businesses turn raw, scattered data into clean, reliable datasets and automated analytics pipelines. My practical experience includes building an end-to-end real estate analytics solution using Python, PostgreSQL, ClickHouse, dbt, Apache Airflow, Grafana, and Docker. I can help you with: • Building ETL/ELT pipelines • Extracting data from APIs, databases, and files • Writing and optimizing SQL queries • Cleaning, transforming, and validating data • Creating dbt models and data quality tests • Automating data workflows with Apache Airflow • Migrating data between databases • Preparing datasets for dashboards and reporting My background in supply management and production operations helps me understand business processes, work carefully with structured data, and focus on practical results. I value clear communication, reliable delivery, and maintainable solutions. If you need help organizing, transforming, or automating your data, I would be glad to discuss your project.

I'm a backend engineer with 4+ years building and scaling production infrastructure for high-growth companies. Currently on the Backend Platform team at BrowserStack (50k+ enterprise customers): • Drove a 208x query speedup (9.6s to 46ms) on a 524M-row table via zero-downtime schema migration • Architected a CDC pipeline (MySQL to ClickHouse) handling 5B+ inserts/updates at 10TB scale • Built an RBAC access-control system from scratch - multi-team hierarchies, 14 enforcement points • Executed zero-downtime primary-key migrations on 1B+ row tables, zero production outages • Remediated SQL injection across 50+ APIs, rolled out CI security scanning covering ~98% of traffic Before that, 3+ years at Zus (0chain) on a blockchain storage platform: • Optimized S3-compatible storage at 500M+ files / 40TB+ scale, sub-100ms latency • Built the Go SDK powering 10K+ concurrent transactions • Cut release cycles from 2 weeks to 3 days with an automated UAT test suite Core stack: Go, Ruby on Rails, Java/Spring Boot, Node.js/Express, Kafka, ClickHouse, PostgreSQL/MySQL/MongoDB, AWS/GCP, Docker, Kubernetes. Open-source contributor (Google Summer of Code 2022 @ Oppia, GNOME Foundation) and competitive programmer (Codeforces Specialist, CodeChef 5-star). Google Cloud Essentials certified. Why work with me: - Production experience at scale - real systems, real users, not tutorials - Track record backed by 100% Job Success and $40K+ already earned on Upwork - Clear communication and measurable, documented performance wins Have a backend, API, or infrastructure problem? Let's talk about it.

I help companies design, build, and scale backend systems that stay fast and reliable as they grow — from monolith-to-microservices migrations to observability platforms that keep engineering teams ahead of production issues. What I bring: - 10 years of Golang expertise — building high-performance, production-grade backend services - Designed and led a 20+ microservice architecture (gRPC-based) for a global ad-tech platform, handling large-scale traffic - End-to-end observability systems (Prometheus, Grafana, Loki/ELK) — built from scratch, adopted across 5+ business teams - Cloud & DevOps: AWS (EKS, S3), Docker, Kubernetes, Jenkins CI/CD — from pipeline design to production deployment - Data layer experience across MySQL, ClickHouse, Presto, and Druid, with strong query optimization skills - 8 years working in global, cross-timezone teams (FreeWhee Global Team) — comfortable owning technical discussions and documentation entirely in English I care about systems that are not just functional, but maintainable — clean architecture, sensible monitoring, and code the next engineer can actually understand. Let's talk about what you're building.

Turning scattered data into actionable dashboards. I am a Data Engineer specializing in robust, end-to-end analytics pipelines. Whether you need to track dynamic market prices, process high-load event streams, or build a scalable data warehouse from scratch, I handle the entire lifecycle—from raw data collection to final visual insights. My Core Stack: Data Processing: Python, FastAPI, dbt, Airflow Databases & Streaming: ClickHouse, Greenplum, PostgreSQL, Kafka/Redpanda, gRPC Collection & Analytics: Custom parsers, API integrations, Dashboarding, Superset, Metabase

I am a Senior Data Engineer with 5+ years of experience delivering production data systems in large product companies and client projects. My work covers the full path from APIs and operational databases to analytics-ready models: ingestion, ETL/ELT, orchestration, batch and streaming processing, data quality, observability, and performance tuning. I take focused assignments where an experienced engineer is needed to build or repair a pipeline, integrate a data source, redesign a data model, or stabilize an existing workflow. I work independently and leave behind maintainable code, documented technical decisions, and a clear handover. Main stack: Python, SQL, Airflow, dbt, Kafka, ClickHouse, PostgreSQL, and BigQuery.

I am a backend developer with over 2 years of experience specializing in building efficient and scalable systems using GoLang. I have worked extensively with databases like PostgreSQL, Clickhouse, and caching solutions like Redis. Additionally, I have experience in distributed systems and event-driven architectures using Kafka. I'm passionate about writing clean, maintainable code and delivering high-performance applications.

I help startups and growing businesses turn ambitious ideas into production-ready, AI-powered applications — and I love every part of that journey, from architecture to deployment. With 5+ years of hands-on software engineering experience, a Bachelor's in Software Engineering, and a Master's underway in Machine Learning & Distributed Systems, I bring both academic depth and real-world enterprise experience to every project. I've built HIPAA-compliant healthcare platforms processing real-time clinical data, engineered LLM-powered backend systems with Retrieval-Augmented Generation (RAG) pipelines, and designed high-throughput data pipelines using Kafka, MongoDB, and ClickHouse. Whatever stage your product is at, I can help you get there faster and more reliably. Skills & Specializations: • Enterprise Web Applications — MEAN & MERN stacks (Angular, React, Node.js, Express) • AI & LLM-Powered Solutions — chatbots, virtual assistants, RAG pipelines, intelligent automation • Microservices & Backend APIs — FastAPI, Node.js, event-driven architecture, Kafka • Data Engineering & Analytics — Kafka, MongoDB, ClickHouse, Apache Superset, PostgreSQL • Cloud & DevOps — AWS, Docker, CI/CD pipelines, monitoring & logging • System Design & Architecture consulting for startups and growing teams Why clients enjoy working with me: • Clean, maintainable code built for long-term scale • Clear communication and a structured, transparent delivery process • A problem-solving mindset — I dig into complex challenges and simplify them • End-to-end ownership, from idea to deployment and beyond I'm excited to bring the same energy and rigor I use on enterprise healthcare and AI systems to your project. Let's talk about what you're building — I'd love to help you move it forward.