Grace Kim

United States0

Analytics Engineer & BI Developer | Microsoft Fabric · Power BI · Python · SQL · DAX | End-to-End Data Pipelines

Data Engineer specializing in BI & Analytics Infrastructure. I build end-to-end data platforms—from ingestion pipelines to executive-facing dashboards—for companies turning fragmented data sources into a single source of truth. I'm currently building the data platform for a global content company, designing a Medallion Architecture (Bronze/Silver/Gold) on Microsoft Fabric that integrates 60+ external ad network APIs into a unified revenue pipeline. The work spans every layer: PySpark ingestion notebooks, Delta Lake MERGE logic, Gold-layer aggregations, and Power BI dashboards with custom DAX measures that leadership now relies on for monthly revenue reporting. Before data engineering, I spent over 7 years as a simultaneous interpreter for C-level executives across industries. That background turned out to be unexpectedly useful—much of data engineering is translation: from business questions into data models, from raw API responses into trusted metrics, from technical trade-offs into language stakeholders can act on. What I bring: • 0-to-1 data platform builds (Bronze/Silver/Gold, Delta Lake, Microsoft Fabric) • Multi-source API integration at scale (60+ ad networks unified into a single schema) • Production PySpark, SQL, and Power BI (DAX, semantic models, matrix-based reporting) • Ad tech and digital revenue domain depth • Bilingual (English/Korean) stakeholder communication

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Experience

Data Engineer (Ads Operations & Corporate Finance)

NAVER WEBTOON

Nov 2025 — Present · United States

Partner directly with the Corporate Finance Head and Ad Operations team to architect the first unified revenue reporting platform across parent and subsidiary entities on Microsoft Fabric. Power BI Dashboards - Designed executive-facing Power BI dashboards (DAX, Power Query) unifying revenue performance, KPI attainment, and YoY variance across parent and subsidiary entities - Built semantic models on star schema (1 Fact + 4 Conformed Dimensions) with optimized DAX and standardized KPI definitions Data Engineering - Reduced manual reporting workflows by ~90% (10+ hrs/week → under 1 hr) via automated daily pipelines integrating 60+ ad networks - Established Bronze/Silver/Gold medallion architecture with data quality validation across the lakehouse 🛠️ Stack: Microsoft Fabric (Lakehouse equivalent to S3 + Databricks + Airflow + dbt unified) · PySpark · SQL · Power BI · DAX · REST APIs · Power Automate · Microsoft Copilot

Business Intelligence Analyst

Applied Medical

Jun 2025 — Aug 2025 · United States

• Drive the entire process of designing and building Power BI reports and visualizations by using Power Query to extract and transform data from various systems, such as SAP HANA Views and SQL databases. • Collaborate within cross-functional teams to define reporting requirements, document business process workflows—including manual steps and pain points—and develop clear resolution roadmaps. • Compile and optimize a list of reports/workspaces to facilitate the transition of Power BI reports to Fabric

Data Analyst (Capstone)

Johnson & Johnson

Jan 2025 — Jun 2025 · Irvine, CA

• Analyze Johnson & Johnson’s historical sales data from over 2,000 hospitals, integrating Medicaid datasets to identify retention trends, at-risk accounts, and untapped market opportunities • Executed advanced customer segmentation and cohort analysis using K-Means clustering, and developed predictive models (XGBoost, Random Survival Forest) to forecast churn risk and high-value accounts achieving 84% test accuracy • Developed interactive dashboards in Tableau and Power BI by integrating Python and SQL pipelines, delivering actionable insights to support sales strategy, marketing, and stakeholder decision-making

Technical Writer - LLM, AI, Localization

Applied Materials

Nov 2022 — Jul 2024

Partnered with engineers, translators, and external vendors to deliver high-quality French-Korean-English datasets suitable for AI translation (LLM) and localization