Thenuka Lawrence
Senior DevOps Engineer at LSEG (London Stock Exchange Group)
Sri Lanka
Summary
🤩
Rockstar🎓
Top SchoolThenuka Lawrence is a Senior DevOps Engineer with 3+ years of hands-on experience designing and operating cloud-native infrastructure, primarily across AWS and Kubernetes. At LSEG he led hybrid cloud migrations and multi-region EKS deployments, cutting file transfer latency by 60% and enabling zero-downtime blue/green releases via GitOps. He automates non-functional testing and NFT pipelines to prevent high-risk releases, turning multi-day test cycles into near real-time risk dashboards. Skilled in Terraform, Ansible, Helm, GitLab CI/CD and Prometheus/Grafana, he also drove database migrations to RDS Oracle and practical cost optimizations early in his career. Based in Sri Lanka, Thenuka blends strong SRE discipline with cross-functional Scrum collaboration and a knack for turning operational pain points into repeatable automation. An observant engineer, he pairs performance testing with dynamic SLA compliance to keep mission-critical systems resilient under pressure.
3 years of coding experience
3 years of employment as a software developer
Bachelor of Science, Information systems, Bachelor of Science, Information systems at University of Colombo School of ComputingSt. Benedict's College, Colombo-13Royal College Colombo
Github Skills (47)
gaussian-mixture-models10
pca10
naive-bayes10
stacked10
random-forest10
factorization10
nearest-neighbors9
r9
spark9
java9
ensemble-learning9
gradient9
python9
svm9
support-vector-machine9
Programming languages (2)
Github contributions (4)
h2oai/h2o3-sagemaker
Mar 2023 - Mar 2023
Integrating H2O-3 AutoML with Amazon Sagemaker
Contributions:9 pushes, 1 branch in 2 days
sagemakeramazon-sagemakerh2oamazonmachine-learning
h2oai/h2o-3
Sep 2022 - Sep 2022
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Contributions:2 commits, 1 PR, 2 pushes in 1 day
xgboostgampythonk-meansautoencoders
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