Technical Skills
Programming Languages & Frameworks
- Python — Object-Oriented Programming (OOP), scripting, automation, and API integrations (e.g., real-time commodity prices like copper)
- PySpark & Pandas — large-scale data transformation, ETL, analytics workflows
- SQL — complex queries including Recursive CTEs, MERGE statements, Directed Acyclic Graphs (DAG), window functions
- Terraform — Infrastructure as Code (IaC) for automating cloud provisioning and environment management
Cloud & Data Platforms
- Azure — Data Factory (pipeline orchestration, dynamic triggers), Databricks (Spark 3.x, Delta Lake, MLflow), Synapse (dedicated and serverless SQL pools)
- Additional Azure services: Blob Storage / ADLS Gen2, Event Hub, Key Vault, Azure DevOps
- AWS — practical hands-on experience during academic projects covering core cloud concepts and foundational services
Data Engineering & BI
- Data modeling following Kimball methodology
- Lakehouse architecture design and implementation
- Building end-to-end ETL pipelines
- Power BI — data modeling, DAX
- Tableau — dashboarding and reporting
Machine Learning Experience
- Long-term ML pipeline support in a previous role, enabling scalable model training and deployment
- Hands-on ML model development with TensorFlow, PyTorch, and scikit-learn during academic projects
Testing & Quality Assurance
- Familiarity with pytest through consulting projects — implemented automated unit and integration tests to improve pipeline reliability
- Developed monitoring and alerting frameworks for proactive data quality and pipeline failure detection
Selected Projects Highlighting These Skills
- Metadata-Driven ETL Framework — reusable, scalable PySpark and Azure Synapse-based ETL with schema drift handling
- ML Pipeline Support — collaborated with data science teams to maintain and improve ML data workflows
- API Integrations — built Python modules connecting to external data sources such as real-time commodity prices (e.g., copper)
- Cloud Learning — completed hands-on AWS projects as part of academic coursework
- Testing Frameworks — assisted with pytest-based automated testing in consulting projects