Maziyar Khorrami-Senior Data Engineer

• Microsoft Azure Data Engineering Certification
• Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure SQL Database, Azure Blob Storage, Azure HDInsight, Azure Stream Analytics, Azure Cosmos DB, Azure Machine Learning, Azure Data Lake Storage
• Google Cloud Platform (GCP), BigQuery, Vertex, BigTable, Cloud Dataflow

• Developed and implemented data pipelines and ETL processes using Apache Spark, Python, and SQL for various data sources such as SAS Viya, Data Warehouses, Hadoop HDFS, and Hive.
• Actively collaborated with stakeholders to analyze data requirements and develop tailored solutions.
• Designed and implemented data pipelines and POCs for ETL processes using Microsoft Azure Blob Storage, Microsoft Azure Functions, Microsoft Azure Data Factory, Microsoft Azure Synapse Analytics, Microsoft Azure Data Catalog, Microsoft Azure Event Grid.
• Responsible for deployment and debugging of PEX files for CLI components.
• Successfully led the migration of an older Hadoop cluster to a new Hadoop cluster. This involved transferring all data, formats, pipelines, CLI integrations, schedules, Airflow DAGs, DB connections, and more.
• Developed PEX files and conducted testing to ensure robustness.
• Implementation and development of a Data Lake for efficient data storage and processing.
• Successful implementation of data protection policies in accordance with GDPR.
• Implementation of IAM and authentication for access control.
• Development of concepts for Data Mesh for effective data management.
• Implementation of data models such as ORM.

Data Analysis

• Creation of Grafana dashboards to monitor data flow and analyze metrics.
• Development of DataDog dashboards to monitor data flow and various metrics such as partition size, tracking of small files, and nodes on the Hadoop cluster.
• Analysis of customer data and search data to identify minor errors in the data between different zones in the Data Lake.
• Analysis of large datasets to identify trends and improvement opportunities.
• Creation of data visualizations and dashboards to present data insights.
• Development of reports and presentations to communicate data findings to stakeholders.

DevOps

• Utilization of GitLab CI/CD for automated pipeline deployment.
• Design and implementation of Docker containers and their templates.
• Development and enhancement of Ansible playbooks for resource and package management.
• Development and use of Jenkins for continuous integration of various PEXs.
• Conducting POCs for Kubernetes and Terraform for container and resource management in the Microsoft Azure using Microsoft Azure Blob Storage, Microsoft Azure Functions, Microsoft Azure Data Factory, Microsoft Azure Synapse Analytics, Microsoft Azure Data Catalog, Microsoft Azure Event Grid.
• Development of Bash scripts under Linux for various purposes including automation of scheduling.

Project Leadership

• Design, development, and execution of an end-to-end test suite to verify the complete and error-free arrival of data from the entire ETL process to target systems.
• Budget management of projects.
• Management of project scope and adherence to regulatory deadlines to meet the requirements of project stakeholders.
• Team leadership and task delegation.
• Definition of stories and epics using agile methods.
• Training of team members to utilize the tools developed.
• Documentation and presentation of results to product owners.

Tech. Stack: Python 3, Hadoop Ecosystem HTP zu CDH, ETL, Terraform, Microsoft Azure Blob Storage, Microsoft Azure Functions, Microsoft Azure Data Factory, Microsoft Azure Synapse Analytics, Microsoft Azure Data Catalog, Microsoft Azure Event Grid, AWS, Data lake, PEX, CLI, Jenkins, Ansible playbooks (Infrastructure as Code), Ambari, CI/CD, GitLab, SQL, Hive ORC / External, PySpark, Airflow, DAG, SCRUM, Kanban, Agile, Jira, BigData, Pro-PyCharm, DBeaver, MSSQL, MySQL, grafana, datadog, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Json, YAML, SQL-Alchemy

• Continued development of an analytical data pipeline based on Python (ETL, ML feature preprocessing, ML model training, results monitoring), designed for managing time series or event-based datasets.
• Data modeling for dimensions and facts.
• Extensive use of Oracle PL/SQL packages for preparing datamarts.
• Data modeling using ORM (Object-Relational Mapping).
• Proof of concept (POC) for utilizing AWS with StepFunction, Lambda, S3, Redshift, and EC2 for cloud-based implementation of ETL and data storage.
• IaC Terraform
• Implementation of Kafka topics for the live stream data pipeline.

Data Analysis

• Analyzed large datasets to identify trends and improvement opportunities.
• Created data evaluations and dashboards to present data insights.
• Developed reports and presentations to communicate data findings to stakeholders.

Data Science

• Developed predictive models (Neural Network, Random Forest, XGBoost, Linear Regression, Stack models) to predict future trends and behaviors (time series, customer data).
• Presented data insights and recommendations to stakeholders.
• Conducted feature engineering for machine learning models.
• Analyzed machine learning models using feature importance.
• Utilized Dataiku for prototyping, creating POCs for machine learning models, and analyzing features and testing various methods and models.

MLOps

• Utilized machine learning models (Neural Network, Random Forest, XGBoost, Linear Regression) in production using AWS Sagemaker, AWS CloudWatch, AWS S3, AWS RedShift, AWS StepFunction, AWS Lambda, AWS Glue.
• Fine-tuned machine learning models with new data in the production environment.
• Periodic retraining.

Team Lead

• Managed project scope.
• Led and trained new team members.
• Defined stories and epics using agile methods.
• Distributed tasks among team members.
• Documented and presented results to product owners.

Tech and Skill Stack: Python, Hadoop Ecosystem, Machine Learning, Supervised Learning, Jupyter Notebook, RStudio, AWS Sagemaker, Terraform, AWS CloudWatch, AWS S3, AWS RedShift, AWS StepFunction, AWS Lambda, AWS Glue, ETL, Kafka, CI/CD on GitLab, Dataiku, Time Series, Oracle, SQL, Hive, Pandas, PySpark, HBase, Tableau, SCRUM, Kanban, Agile, Jira, BigData, Pro-PyCharm, Requirements Analysis, Numpy, Scikit, GridSearch, Anomaly Detection, statistical modelling, multivariate analysis, exploratory data analysis, XGBoost, Random Forest, Matplotlib, Seaborn, Linux, Bash, R, RStudio, MapReduce PowerBI, Tableau, Confusion Matrix, Feature Importance, Neural Network, XGBoost, Decision Tree, Time Series, Grid Search, Model Fine Tuning, Random Forests, Logistic Regression, Stacked Models, Model Retraining, Dataiku, MIFlow, Scikit-Learn, Pandas, Python, Jupyter Notebook

Recipient of the People Award 2020 from Telefonica Germany [as a member of the ChurnLab team] for outstanding customer churn reduction

Web application development.

NodeJS, React, Git, VSCode, SCRUM

Application development in MVC using JEE7 and PrimeFaces.

JEE7 (JPA, JSF, EJB), Primefaces, OmniFaces, Maven, SVN, MySQL, SCRUM, Payara

Backend development for the document management department in JEE 7.

JEE7 (EJB, JPA), SCRUM, Hibernate, JBoss5, Maven, Solid DB, WSDL, XSD, Eclipse, Git, Jira, Mockito, Arquillian, SOAP-UI, SOAP, AXIS II

Software development in frontend.

Vaadin 7, Java, Eclipse, JPA, MSSQL, PostgreSQL, JPQL, Hibernate, Maven, Git, Glassfish

Troubleshooting for Tivoli Storage Management (IBM Software).

Ubuntu 12.04, Linux, Ubuntu 10.4, TSM, SSH, Bash, Vim