Vadim Y.

🔷 𝗟𝗮𝗿𝗴𝗲-𝘀𝗰𝗮𝗹𝗲 𝗱𝗮𝘁𝗮𝘀𝗲𝘁𝘀 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝗱 𝗿𝗲𝗹𝗶𝗮𝗯𝗹𝘆. 𝗘𝗧𝗟/𝗘𝗟𝗧 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 𝘁𝗵𝗮𝘁 𝘁𝘂𝗿𝗻 𝗺𝗮𝗻𝘂𝗮𝗹, 𝗿𝗲𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗱𝗮𝘁𝗮 𝘄𝗼𝗿𝗸 𝗶𝗻𝘁𝗼 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻. 𝗗𝗮𝘁𝗮 𝗰𝗹𝗲𝗮𝗻𝗶𝗻𝗴 𝗵𝗮𝗻𝗱𝗹𝗲𝗱 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝘄𝗶𝘁𝗵 𝗟𝗟𝗠𝘀. Senior Big Data Engineer and Python Data Engineer with 7+ years building ETL/ELT Pipelines, Spark and PySpark data processing, and Data Warehousing on Snowflake and BigQuery for teams that need their data accessible, meaningful, and secure - at scale. If your team is drowning in raw data, stitching pipelines together by hand, or waiting on slow reports - I build Data Engineer infrastructure and AI/LLM Engineering that make that disappear. 🎯 𝗪𝗵𝗮𝘁 𝗜 𝗗𝗼 𝗕𝗲𝘀𝘁: 🛠 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 & 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 End-to-end Data Engineer pipeline design: extraction, transformation, loading, orchestration, and monitoring. I build ETL/ELT Pipelines with Spark, PySpark, Airflow, Dagster, and dbt, with infrastructure managed through Terraform, Kubernetes, and Docker. Full logging, alerting, and failure recovery included as standard - so ETL/ELT Pipelines run without babysitting. 📦 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 & 𝗟𝗮𝗿𝗴𝗲-𝗦𝗰𝗮𝗹𝗲 𝗗𝗮𝘁𝗮 As a Python Data Engineer, I design and maintain Data Warehousing on Snowflake and Google BigQuery, and handle large-scale datasets with Cloudera, Hive, MR2, and Spark. Query optimization, partitioning, and data modeling keep everything fast and clean. 🐍 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 & 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗶𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 Deep SQL experience across MySQL, PostgreSQL, and ClickHouse. As a Python developer, I build with Pandas, Polars, and SQLAlchemy, and ship web services in Flask, FastAPI, and Django - with Celery and Redis for async processing and caching in production. ✨ 𝗟𝗟𝗠-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 As an AI/LLM Engineer, I work with LLMs and LangChain to build intelligent pipelines - data-cleaning automation, chatbots, and AI-powered workflows dropped straight into your Big Data Engineer infrastructure. 📈 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 & 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 Looker, Apache Superset, and Looker Studio dashboards wired directly to your ETL/ELT Pipelines - so business teams get clean, decision-ready outputs without touching raw data. 🔧 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸: Python · SQL · Pandas · Polars · PySpark · Spark · Airflow · dbt · Dagster · SQLAlchemy · Flask · FastAPI · Django · Celery · Redis · BigQuery · Snowflake · PostgreSQL · MySQL · ClickHouse · Cloudera · Hive · MR2 · GCP · Terraform · Kubernetes · Docker · LangChain · Looker · Apache Superset 🏁 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗬𝗼𝘂 𝗚𝗲𝘁: - ETL/ELT Pipelines that replace slow, manual data work with automation - Data Warehousing on Snowflake and BigQuery, built to scale - Faster queries through BigQuery optimization and partitioning - Automated data cleaning and reporting powered by AI/LLM Engineering - Clean, decision-ready dashboards used across whole teams 👥 𝗪𝗵𝗼 𝗜 𝗪𝗼𝗿𝗸 𝗕𝗲𝘀𝘁 𝗪𝗶𝘁𝗵: - Startups building Big Data Engineer infrastructure from scratch - SaaS teams automating ETL/ELT Pipelines and reporting - Companies modernizing Data Warehousing on Snowflake or BigQuery - Teams replacing manual data work with Spark and PySpark pipelines - Businesses adding AI/LLM Engineering to existing data infrastructure 💬 If you want a technical partner who works as both a reliable Python Data Engineer and a forward-thinking AI/LLM Engineer - someone who builds data systems that run reliably, scale effortlessly, and drive better decisions - 𝗹𝗲𝘁'𝘀 𝗰𝗼𝗻𝗻𝗲𝗰𝘁.