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jiyooonkim/README.md

Grace Kim

Senior Data Engineer

Data Engineer with 8+ years of experience building scalable data platforms, distributed ETL pipelines, cloud architectures, and high-performance analytics systems. Proven track record delivering reliable data foundations across e-commerce, logistics, media, and enterprise environments.

Specialized in designing end-to-end data ecosystems from ingestion to warehouse modeling, orchestration, optimization, and data quality governance.


Core Expertise

  • Data Platform Architecture
  • ETL / ELT Pipeline Engineering
  • Data Warehouse / Data Mart Modeling
  • Batch & Near Real-Time Processing
  • Workflow Orchestration / Automation
  • Query Performance & Cost Optimization
  • Data Quality / Validation Frameworks
  • Cloud Migration / Modernization
  • Business Intelligence Enablement

Tech Stack

Languages
Python, SQL, Bash, Java

Data Engineering
Apache Spark, Hadoop, Hive, Sqoop, Airflow

Cloud / Platform
AWS (S3, Glue, Athena), GCP (BigQuery, GCS, Compute Engine), Databricks, Docker, Kubernetes

Databases
MySQL, OLTP / OLAP, Delta Lake, Hadoop, S3

Collaboration / DevOps
Git, GitLab, Jenkins, Jira, Confluence, wiki, Slack, teams


Career Highlights

  • Built enterprise-scale pipelines processing multi-domain business data
  • Improved ETL and query performance through partitioning, tuning, and architecture redesign
  • Reduced manual operations through orchestration and automation frameworks
  • Established trusted data models for analytics and decision-making
  • Delivered scalable systems supporting reporting, dashboards, and AI use cases

Current Focus

  • Modern Data Stack
  • Streaming Architecture
  • ML / AI Data Infrastructure
  • Search & Recommendation Data Systems
  • Scalable Cloud-Native Data Engineering

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