Renato Gálvez Castillo Email and Phone Number

- Develop a strong understanding of company domains, strategic direction, and user needs.- Help define a state-of-the-art hybrid cloud data infrastructure.- Set up data pipelines from a multitude of systems into our cloud platform.- Provide direction to data engineering and architecture in selecting the right tools for the right jobs.- Collaborate on requirements and determine appropriate: dimensional modeling, ETL pipelines, large-scale distributed ETL pipelines, migration of data across multiple data repositories, and enable large-scale machine learning.- Create and maintain analytics pipelines that generate data + insight to power business decision-making.- Bootstrapping a data engineering team at an early stage in the team’s evolution.- Evaluate, compare, and improve different approaches, including innovation of design patterns, data lifecycle design, data ontology alignment, annotated datasets, and elastic search approaches.- Prepare data for the data scientist exploration and discovery process. - Data wrangling/munging for downstream analytics.- Assemble large, complex data sets that meet functional / non-functional business requirements.- Identify, design, and implement internal process improvements: automate manual processes, optimize data delivery, re-design infrastructure for greater scalability, etc.- Build the infrastructure required for optimal extraction, transformation, and loading of data from various sources.- Work with stakeholders, including Executive, Product, Data, and Design teams, to assist with technical issues and support their data infrastructure needs.- Work with data and analytics experts to strive for greater functionality in our data systems

- Build and run docker environments- Work with publishing services in Serverless- Develop ETL services (Extraction, Transformation, and Loading of data)- Work with Terminal Data structures and algorithms- Develop API/REST/GraphQL consumption- Use CronJobs Git and Github- Develop modules with Python Testing- Handling data storage in Data Warehouse / Datalake / Database Automation of database maintenance

- ETL design and development.- Develop queries in AWS Aurora- Develop queries in AWS Redshift- Work with monitoring tools- Work with containerization like Docker or Kubernetes- Set up an environment in Terraform and AWS CloudFormation.- Handle DevOps tools and principles including version control, Infrastructure as code and deployment pipelines- Work with data analytics application administration- Elaborate ML pipelines with python.

- Carry out the information gathering on the needs of the business areas.- Interpret business requirements and document them through functional and technical specifications.- Analyze data from different sources to extract information.- Model the collected information into efficient data structures.- Design, develop, test and deploy processes of extraction, transformation, and loading (ETL) of structured and unstructured data to the cloud.- Develop and maintain robust and reliable data pipelines.- High volume information processing using big data technologies in the cloud.

- Maintained a State Bar Departments' database master files, including resolving split records, entering corrections, verifying database update reports, monitoring registration systems, case management and performing systematic searches for incorrect data.- Work with standard computer tools, designs, develops and executes queries of State Bar databases and develops additional databases as necessary to complete queries. Supervise the design and preparation of various statistical reports. - Review and check how statistics and information, that pertain to a Department, are gathered, organized and processed.

• Transformation and analysis of data into useful, timely, and reliable information that will serve for decision-making, supported by the use of available IT tools (Google Big Query, PL / SQL, Google Cloud Storage).• Analysis, design, and development of indicators for the areas that request support with information extracted from the various computer systems implemented in the institution.• Extraction and selection of different variables, creation, and optimization of classifiers through machine learning. (Python / R)• Process, clean and verify the integrity of the data used for the analysis processes. Construction and improvement of pipelines.• Build operational, tactical and managerial management dashboards (Google Data Studio, Power BI).

• Establish product universes and sample design through sampling techniques.• Database management for establishing sales projection through statistical models of time series (SQL Server 2016, Tableau).• Statistical support in data consistency/analysis of variables / Coverage Analysis (Python, R, SPSS)• Implementation of process improvement projects under Six sigma methodology• Responsible for the statistical control of the processes in the area (Minitab).• Statistical support in meetings with external and internal clients

• Management of information from the database for the analysis of statistical control of the quality of the processes (Minitab)• Development and maintenance of statistical models for the validation of processes.• Implementation and monitoring of management indicators (SPSS, R).• Elaboration of process improvement projects using quality tools, Six Sigma, and 5s methodology.• Internal auditor based on the ISO 9001: 2008 standard and BPM manual• Implementation and maintenance of the Integrated Management System: scheduling of internal audits, external audits, updating of procedures, instructions and records corresponding to all areas.