Transform your data engineering practice with comprehensive DataOps automation skills that eliminate manual processes, reduce errors by 70%, and accelerate deployment cycles. This specialization teaches you to build production-grade data systems using Git workflows, Docker containerization, CI/CD pipelines, Ansible automation, Airflow orchestration, and advanced debugging techniques. Through hands-on projects simulating real enterprise environments, you'll develop the automation expertise that distinguishes senior data engineers who architect resilient, scalable data platforms from those still managing systems manually.
Applied Learning Project
Apply DataOps principles through real-world scenarios including resolving complex Git conflicts in collaborative data projects, containerizing data applications with Docker, implementing CI/CD pipelines for automated testing and deployment, orchestrating multi-step ETL workflows with Airflow, automating database operations with stored procedures, and debugging production data anomalies. Each project simulates challenges faced at companies like Netflix and LinkedIn, where you'll build automated solutions that reduce manual intervention from hours to minutes.
