Dan has an extensive experience in DevOps, Site Reliability Engineering, Cloud Infrastructure Management, and Chaos Engineering. He is a Certified DevOps and Chaos Engineer in AWS, Azure, and GCP. As a DevOps Architect, he designs, architects and implements CI/CD with DevOps principles by using various DevOps tools like Git, Docker, Podman, Ansible, Kubernetes, OpenShift, Istio and Terraform in a hybrid/multi-cloud environment. He also possesses various domain expertise like eGaming, Retail, Banking, e-commerce, R&D, Mobility Communications Networks, and AI Connected Cars. If you are interested in becoming a DevOps/SRE/Chaos Engineer and you are interested in learning more about it, he can help you.
Years of Experience: 9 Years
What does being a mentor means to him:
Dan is passionate about building capabilities within each individual and believes that there is no end to learning. He spends his time learning and growing and helps others grow who are interested in becoming the next-gen DevOps/SRE/Chaos Engineering with AI/MLOps.
What is his advice to someone considering a future in technology?
DevOps, Site Reliability Engineering and Choas Engineering are just bewildering, with these skills in your belt you can work in a wide range of industries in Tech and Engineering. You can master these technical skills to accomplish amazing things.
Key strengths: Artificial Intelligence for IT Operations (AIOps), Machine Learning Operations (MLOps), DevOps, Python, Chaos Engineering, and Site Reliability Engineering.
Mortgage data is complex to handle due to its volume and stored inconsistently at varying time intervals. Data maintenance will be tedious for the organization, and it also subjects in deviation of tracking foreclose, forebear and buy/sell portfolio. A large mortgage servicer in North America enabled portfolio & mortgage analytics to build large voluminous data repository based on specific constraints.
Maveric’s datatech team worked with the organization to analyze its unstructured data, and developed analytics workflows to extract meaningful data with the help of data stores which were powered by Oracle and Mongo.
Explore how we took this challenge and provided feasible solution with our proactive mortgage predictive model to ease the decision-making process developed within stringent SLA’s.