Technical Arsenal

A blend of data science, engineering, and cloud expertise.

Core Competency Overview

Cloud & Data Platforms

  • Azure Architecture (Expert Level)
    Expert-level design & implementation of secure, scalable, and resilient cloud solutions (VNet, Compute, Storage, Governance, Security). Validated by Azure Solutions Architect Expert certification.
  • Azure Data Services
    Azure Databricks, Synapse Analytics, Data Factory (Pipelines & Data Flows), Data Lake Storage Gen2, Stream Analytics.
  • Data Governance Microsoft Purview, Unity Catalog for metadata management, data discovery, and lineage.
  • Infrastructure as Code (IaC) ARM Templates, Bicep for automated and repeatable environment provisioning.
  • Cloud Administration & Security Azure Monitor, Log Analytics, Application Insights, Azure Security Best Practices. Validated by Azure Administrator Associate certification.

Data Engineering & MLOps

  • Big Data & Lakehouse
    Apache Spark (PySpark), Delta Lake for building reliable and high-performance data lakehouses.
  • ETL/ELT & Warehousing Design of robust data pipelines and dimensional models. Validated by Azure Data Engineer Associate certification.
  • Databases SQL & NoSQL (SQL Server, Cosmos DB).
  • MLOps & Automation
    End-to-end ML lifecycle management including CI/CD (Azure DevOps, GitHub Actions), model deployment, monitoring (Azure ML, MLflow), and implementing Responsible ML.
  • Containerization Docker and Kubernetes for packaging and deploying applications.

Data Science & AI

  • Generative AI
    Solution design and development using Azure OpenAI Service, Large Language Models (LLMs), and prompt engineering.
  • AI Engineering
    Implementing solutions with Azure AI Services (e.g., Vision, Speech) and Azure AI Search. Validated by Azure AI Engineer Associate certification.
  • Machine Learning Supervised & Unsupervised Learning (Regression, Classification, Clustering), Feature Engineering, Deep Learning (TensorFlow, PyTorch).
  • Core Data Science Python (Pandas, NumPy, Scikit-learn), SQL, Statistical Modeling, NLP (NLTK, Hugging Face).

Business Intelligence

  • Power BI
    End-to-end BI solution development from data modeling and Power Query (M) to advanced DAX calculations and interactive report design.
  • Data Visualization Best practices for creating actionable insights and compelling data stories.
  • Stakeholder Engagement Translating business requirements into technical specifications and BI solutions.

Essential Technologies & Methodologies

  • Programming Python, SQL, PySpark; R, Scala, Java, C#
  • Development Practices Agile/Scrum, Version Control (Git), Product Management.
  • Business & Leadership
    Stakeholder Communication & Presentation, Project Leadership, Team Collaboration & Mentoring, Technical Documentation.