Responsibilities & achievements

Data Architecture Design: Crafting and refining data architecture plans to ensure effective and efficient data handling ▪ Implement solutions Frontend/Backend using Docker, docker file, docker composer. ▪ Cloud-to-Cloud Migrations: Executing migrations of data pipelines between cloud platforms utilizing containers and Python for seamless transitions. ▪ Data Architecture Implementation: Putting into action the defined data architecture plans, including design and specification. ▪ Data Pipeline Migration: Transitioning data pipelines to GCP and Azure cloud environments, utilizing services such as Bigquery, DataFusion, Composer, Cloud Functions, PowerBI, GKS, Python. ▪ Utilizing Azure Services: Implementing solutions with Azure services like Azure Databricks, Azure Data Factory, Azure Kubernetes Service, Azure Data Lake Gen2, Pyspark, Spark, SQL, Postgresql, and Azure DevOps (ADO). ▪ Frontend Development: Utilizing technologies such as React and Poetry for frontend development. ▪ Project Management: Utilizing project management tools like Jira to plan and track progress throughout the project ▪ Data Mapping and Modeling layers. ▪ Data extraction, data loading, and data transformation using Pyspark. ▪ Streaming jobs using Pyspark. ▪ Incremental and bulk data updates. ▪ Set up monitoring and alerting mechanisms. ▪ Development build and deployment scripts ▪ Product support and documentation maintenance

Responsibilities & achievements

▪ Technical management of the teams. ▪ Increment Plan Definition: Creating a comprehensive plan for incremental project development and implementation. ▪ Identification of risks, resolution, negotiation, and agreements with the client. ▪ Management of teams composed of data scientists, data engineers, full-stack developers, data governance professionals, and BI experts. ▪ Conflict Resolution: Addressing and resolving conflicts and issues that may arise during the project to ensure a harmonious working environment. ▪ Architecture Component Definition: Identifying and specifying the essential architectural components necessary for the project's success. ▪ Negotiation and Agreements: Engaging in negotiations with the client and team members to establish project requirements and secure mutually agreed-upon terms. ▪ Team Management: Efficiently managing cross-functional teams comprising data scientists, data engineers, full-stack developers, data governance specialists, and business intelligence (BI) experts. ▪ Monitoring and logging of pipeline activities using Rocket's built-in monitoring features. ▪ Implementation of general software and data fabric solutions using the Stratio Data Factory platform

Responsibilities & achievements

Migrating Data Warehouse (DWH) Solution: Transitioning the existing Data Warehouse solution to new GCP (Google Cloud Platform) solutions, with a particular focus on leveraging Bigquery o DWH Modeling and Implementation: Employing best practices for Data Warehouse modeling while implementing the DWH solution in Bigquery. o Reverse Engineering: Conducting reverse engineering activities to understand the structure of the current DWH solution, including analyzing the business ETL (Extract, Transform, Load) processes. This involves using tools such as Informatica Power Center and Neetiza. o ETL Implementation: Using Google DataFusion for ETL (Extract, Transform, Load) tasks, including data ingestion and transformation processes. o Workflow Orchestration: Utilizing Google Composer to orchestrate and manage the workflows within the new DWH solution, ensuring data flows smoothly and efficiently o Design and modeling of the data solution in BigQuery, data warehousing. o Migrate the data from on-premises (Netezza) to GCP BigQuery. o Building ETLs using Data Fusion, Pub/Sub for data ingestion, Airflow for orchestration, Python for transformations, and metadata extraction. o Implement the DAGs in Airflow. o Analyze the existing data solution through reverse engineering and replicate the model in the new solution.

Responsibilities & achievements

Implement the core to migrate the business processes from onpremises to AWS Cloud by implementing processing jobs on computing solutions on AWS and orchestrating them with Step Functions, along with other components like S3, Redshift, and Segment. o Implement software solutions in AWS for the analytics team using various AWS services. o Migration of Business Processes to AWS: Implementing the core infrastructure to migrate business processes from on-premises to AWS Cloud. This includes setting up computing solutions on AWS and orchestrating them using AWS Step Functions. Key Cristian Tovar Data Engineer 6 AWS components like S3, Redshift, and Segment will be utilized in this process. o Support for Data Solutions and Analytics: Providing support for data solutions, analytics, and reporting requirements. Assisting the IT team in the telecommunications industry by implementing data solutions using AWS Analytics services. This includes Lambda, S3, CloudFormation, EMR (Elastic MapReduce), AWS Glue, AWS Catalog, Lake Formation, Kinesis Firehose, RDS (Relational Database Service), SQS (Simple Queue Service), SNS (Simple Notification Service), Step Functions for workflow orchestration, Redshift, Athena, API Gateway, QuickSight, CloudWatch, DynamoDB, and other data tools like Talent and Segment. o ETL Solution Migration: Migrating the current ETL (Extract, Transform, Load) solution from Talent to AWS, ensuring a seamless transition of data processing tasks.

Responsibilities & achievements

Development of Business Process Optimization Strategies: Undertaking the role of devising optimization strategies for business processes within big data platforms, with a focus on the Cloudera ecosystem. ▪ Role Description: Working as a Big Data Developer, the responsibilities include the implementation of business processes utilizing the Hadoop ecosystem, which consists of components like HIVE, HUE, Impala, Spark, Zookeeper, Sqoop, Oozie, HDFS, and more. These processes are executed on a Cloudera distribution. Furthermore, Spark is utilized for batch processing in a distributed manner, with a strong emphasis on using Python and Scala as the programming languages of choice

Responsibilities & achievements

▪ Software Development for Jubilation Projects: Serving as a developer for Jubilation's software on projects dedicated to Colombian companies. This involves actively participating in the design and coding of software solutions tailored to meet the specific needs of clients. ▪ Development of Decision Rules Engine Using Drools: Creating a decision rules engine utilizing Drools, a rules engine for Java applications, to enable intelligent decision-making processes within software solutions. ▪ Role Description: The role entails implementing new functionalities across both the backend and frontend layers of an application built with a microservices architecture. For the backend, Java version 8 is used, with the PlayFramework employed to implement web service methods. The database utilized is Oracle, and RabbitMQ serves as the message broker for efficient communication. On the frontend, React.js is the framework of choice, utilizing JavaScript and following the Redux pattern to manage user actions and flow. The entire stack, including the technologies mentioned, is deployed on the AWS Cloud infrastructure. ▪ solutions on projects in different areas. ▪ Update project framework Play 2.7 with libraries for tracing. ▪ Report developer using the standard defined by Colombian government institutions.

Responsibilities & achievements

Analyzer for test scenario requirements ▪ implement functional (Test Cafe) and unit test automation using Xunit framework. ▪ Unit Test Development with ASP.NET Framework: Functioning as a unit test developer, responsible for creating unit tests specifically tailored for a web application constructed within the ASP.NET framework. These tests are crucial to validate the functionality and performance of the application. ▪ Analysis of Test Scenario Requirements: Serving as an analyzer for test scenario requirements, undertaking a comprehensive assessment to understand the specific requirements and expectations related to the testing process. ▪ Functional and Unit Test Automation: Implementing automation for both functional and unit testing, utilizing the Xunit framework for test automation. These tests are carried out on a web application developed using the .NET framework, with the addition of C++ for specific components. The goal is to ensure the thorough testing of the application's functionality, guaranteeing its reliability and efficiency

Responsibilities & achievements

▪ Implement new functionalities in backend and frontend layers in an application with monolithic architecture using Java ▪ Using Vaadin framework to create the client interaction. ▪ Using Spring framework to define the backend and the MVC pattern ▪ Using Mybatis implement the ORM entities. ▪ Leading a small dev team. ▪ Full Stack Developer: Functioning as a full stack developer, with responsibilities spanning both the frontend and backend layers of software development. ▪ Development of ERP Solutions: Specializing in the development of ERP (Enterprise Resource Planning) solutions for projects across various sectors, including banking, the public sector, city halls, and government entities. ▪ Implementation of New Functionalities: Focusing on the implementation of new functionalities within the software, this role covers both the backend and frontend aspects of an application. ▪ Monolithic Architecture: Working with an application architecture structured as monolithic. The backend is constructed using Java, incorporating key frameworks and technologies such as the Vaadin framework for client interaction, the Spring framework to define the backend, and the utilization of the MVC (Model-View-Controller) pattern through spring-webmvc. Furthermore, Spring modules are employed for various purposes, including spring-web to implement and expose web services, spring modules like mybatis-spring using XML mapper to write complex SQL queries, and springjdbc and spring-tx to define the persistence and data access layer, facilitating the creation of low-level services. All of these components are configured across bean definitions with declared XML using Spring modules such as Spring Core and Context.