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Hi 👋 My name is Christopher Shehu

🚀 Passionate Data Engineer | 💾 Building Scalable Data Pipelines | 📊 Transforming Raw Data into Insights | 🌐 Cloud Enthusiast | 🔧 Open Source Contributor

Welcome to my GitHub Portfolio! I'm a dedicated Data Engineer with expertise in designing, implementing, and maintaining robust, scalable data pipelines that transform raw data into actionable insights. I have a strong background in data engineering, cloud technologies, and open source contributions, and I'm always looking to learn more and grow in the field.

Skills

🔧 Data Engineering Tools: Apache Spark, Apache Kafka, Apache Flink, Apache Airflow, Hadoop, Databricks, Delta Lake, Data Factory

💻 Programming Languages: Python, Scala, SQL

🌐 Cloud Platforms: AWS, GCP, Azure

🗃️ Databases & Storage: PostgreSQL, MySQL, Amazon S3, Google Cloud Storage, Microsoft SQL Server, Azure Data Lake, Delta Lake

🚢 Containerization & Orchestration: Azure Data Factory

📈 Data Visualization: Power BI, Plotly

🔒 Data Security & Compliance: HIPAA, Azure Key Vault

Certifications

📜 Microsoft Certified: Azure Fundamentals - Demonstrated foundational understanding of cloud services and how they are provided using Microsoft Azure.

📜 Microsoft Certified: Azure Data Fundamentals - Validated foundational knowledge of core data concepts, including relational and non-relational data.

📜 Databricks Lakehouse - Proven expertise in building and managing modern data platforms using Azure Databricks and Delta Lake.

📜 Epic Certifications:

  • Ambulatory: Proficiency in implementing and configuring Epic's outpatient electronic medical record system.
  • Reporting: Expertise in creating reports and data analysis using Epic's reporting tools.
  • SQL: Demonstrated skills in writing SQL queries and managing databases within the Epic ecosystem.
  • Healthy Planet: Proficiency in Epic's population health management module, which supports care management and coordination.

📜 CompTIA Project+ - Certified knowledge of project management best practices, including project planning, execution, and closure.

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Christopher Shehu's Projects

data-engineering-wiki icon data-engineering-wiki

The best place to learn data engineering. Built and maintained by the data engineering community.

dbldatagen icon dbldatagen

Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines

dlt-meta icon dlt-meta

This is metadata driven DLT based framework for bronze/silver pipelines

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