Mufide Palaoglu Yesiltas

About Mufide Palaoglu Yesiltas

I am a with extensive experience in designing, developing, and optimizing cloud-native data solutions. Throughout my career, I have focused on building scalable architectures that unlock the full potential of enterprise data, particularly within the Microsoft Azure ecosystem:• (Azure Data Factory, Synapse Analytics, Data Lake, Serverless & Dedicated SQL Pools)• (Delta Lake, Medallion Architecture, PySpark, SQL Warehouses)• (Advanced Data Modeling, DAX, Performance Tuning, Row-Level Security)• & (ETL/ELT frameworks, CI/CD pipelines, Unity Catalog, Data Quality strategies)Currently, I am dedicated to driving innovation in scalable cloud data engineering while contributing to initiatives that connect data engineering, advanced analytics, and AI-powered insights.

Experience

1. Senior Data Engineer

   Burlington Stores, Inc.

   Feb 2024 — Present · Chicago, IL, US

   Built end-to-end data pipelines using Azure Data Factory and Azure Databricks, implementing medallion architecture on Delta Lake• Developed Lakeflow Declarative Pipelines for real-time and batch data processing with auto-scaling clusters and Photon Engine optimization, reducing processing time by 45%• Configured Unity Catalog for centralized data governance with access controls, data lineage tracking, and cross-workspace data sharing across dev, staging, production environments• Built metadata-driven ingestion framework in Azure Data Factory with parameterized pipelines orchestrating Databricks notebook activities for 15+ source systems including SQL Server, Oracle, and flat files• Implemented Auto Loader for incremental file ingestion from ADLS Gen2, processing streaming data with schema evolution and exactly-once guarantees using Structured Streaming• Developed PySpark and Spark SQL notebooks with MERGE INTO for upserts, SCD Type 2 handling, and OPTIMIZE/VACUUM/Z-ORDER for Delta table maintenance• Implemented data quality checks using Lakeflow pipeline expectations with quarantine patterns for failed records, ensuring data integrity across medallion layers• Configured Databricks Workflows for orchestration of complex multi-task Job Clusters with dependencies, retries, and alerting via Logic Apps for proactive issue detection• Created Databricks SQL Warehouse views and dashboards serving 100+ business users with optimized query performance leveraging Photon Engine• Created Power BI reports connected to Databricks SQL Warehouse with DirectQuery, DAX measures, and Row-Level Security • Supported CI/CD pipelines using Databricks Repos and Azure DevOps with Databricks Asset Bundles for automated deployment across dev, staging, and production environments• Leveraged Microsoft Fabric Lakehouse with OneLake and Direct Lake semantic models for analytics layer, enabling real-time Power BI dashboards on top of Databricks Delta tables without data refresh latency

Education

• Istanbul Sabahattin Zaim University

  Bachelor's degree, Software Engineering