I help businesses turn raw, scattered data into clean, automated, and analysis-ready systems combining hands-on Data Engineering, DevOps, and Cloud expertise to build pipelines that actually run reliably in production.
What I offer:
Data Engineering & Big Data: I design and build ETL pipelines using Spark and SQL, implementing the Medallion architecture to progressively clean and structure data from bronze (raw) to gold (analytics-ready) layers. I work with structured and unstructured data at scale, optimizing storage and query performance for big data workloads.
Cloud Engineering (Azure, AWS, GCP): I build and deploy scalable, cost-effective cloud architectures across Azure, AWS, and GCP. This includes setting up data warehouses, cloud-native applications, and infrastructure provisioning using tools like Terraform.
DevOps & Automation Systems: I set up CI/CD pipelines and automation systems (Jenkins, GitHub Actions) that take manual, error-prone deployment processes and turn them into fast, reliable, automated workflows I've cut release cycles by 60% using this approach. I also containerize applications with Docker for consistent, reproducible deployments.
Data Analysis & Statistical Analysis: Using Python, SQL, and R, I clean and analyze datasets to uncover key trends, run regression and statistical analysis, and translate findings into clear, actionable insights.
Machine Learning: I build and apply ML models for prediction and pattern recognition tasks, using Python-based workflows integrated directly into the data pipelines I build.
What sets me apart: I don't just build isolated dashboards or scripts I understand the full path from raw data to business decision, so I can own a project end-to-end: ingesting and cleaning data, automating the pipeline, deploying it reliably, and delivering the analysis or dashboard on top. I bring real production experience (Azure Databricks, Spark, Power BI, CI/CD) rather than just tutorial-level knowledge.
Whether you need a one-time data cleanup and analysis, a fully automated pipeline, or ongoing DevOps/DataOps support, I'm ready to help you build systems that are efficient, reliable, and built to scale.