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As a data and cloud specialist, Julio leverages his skills in Python, R, Spark, Databricks, Terraform, Kubernetes, Airflow, and various AWS and GCP services to build scalable, reliable, and secure data pipelines and machine learning models. He is proficient in CI/CD, GitOps, Agile methodologies, and data visualization tools. He is passionate about delivering value and innovation to his clients and empowering them with data-driven insights and solutions.

Technical and Functional Skills

• CI/CD: GitOps, Gitlab Pipelines, GitHub Actions, AWS CodePipeline, AWS CodeBuild, AWS Elastic Beanstalk, AWS Step Functions, GCP Cloud Build, Apache Airflow
• IaC: Terraform Cloud and OSS, AWS CloudFormation
• DataOps: Databricks (Apache Spark), Hadoop , GCP Dataflow, GCP Dataproc, GCP Pub/Sub, GCP Cloud Functions, Apache Beam, AWS Glue Jobs, AWS Lambda Functions
• Databases: MySQL, PostgreSQL, GCP products (Cloud Storage, Cloud Bigtable, BigQuery), AWS products (S3, RDS, Amazon Aurora, DynamoDB, Redshift, DMS, ElastiCache).
• Programming languages: Python (PySpark, NumPy, Pandas, Scikit-learn, NLKT, TensorFlow, OpenCV, Flair, Torch), R, JavaScript, C# (basic).
• Agile: Scrum Master Certified, Lean Six Sigma, Jira.
• Containerisation: Docker, Kubernetes, Helm Charts, GCP products (Cloud Run, GKE), AWS products (Fargate, EKS, ECS).
• Machine learning models: Polynomial Regression, Random Forest (Regression), Logistic Regression, SVM (Classification), Clustering, PCA (Unsupervised), NER, sentiment analysis (NLP), Large Language Models (LLMs).
• MLOps: Kubeflow, MLFlow, Amazon SageMaker MLOps, GCP Vertex AI.
• Data visualisation: Google Data Studio, PowerBI, Tableau, Python and R libraries, Storytelling with Data best practices.
• Finance: Bloomberg Market Concepts certification, cost accounting & optimisation, financial administration &n engineering, investment theories, economics.