Alejandro Romero Moya

Data Engineer within the Bank of Spain's Data Lake, participating in multiple critical collections (CSDB, CSEC, Bizum, Employment Histories, among others) and developing distributed ELT pipelines in the Cloudera ecosystem.

My work covers end-to-end development of data processes, combining engineering, automation, and quality assurance in high-volume environments.

Main responsibilities:

Design and implementation of ELT pipelines with DBT, Spark, Hive, and Impala, working on HDFS and Iceberg tables.

Automation and orchestration of processes using Control-M and Bash scripting.

Data preparation, validation, and normalization, ensuring its integration into corporate systems.

Component parameterization using YAML, dependency management, and flow configuration.

Version management and multi-environment deployments (DEV, TEST, STAGING, PROD) with Git and Bitbucket.

Monitoring, troubleshooting, and incident resolution in large-scale distributed processes.

Contribution to technical standards and best practices within the data engineering area.

Working with large data volumes in distributed architectures, optimizing pipeline performance, stability, and maintainability.

Working within the Bank of Spain's Data Lake, participating in multiple critical data collections (CSDB, CSEC, Bizum, Employment Histories, among others) and building distributed ELT pipelines in the Cloudera ecosystem. My work combines end-to-end data engineering, automation, and quality assurance for high-volume flows.

Main responsibilities:

Design and implementation of ELT pipelines with DBT, Spark, Hive, and Impala, working on HDFS and Iceberg tables.

Automation and orchestration of processes using Control-M and Bash scripting.

Preparation, validation, and normalization of data collections, ensuring their integration into corporate environments.

Parameterization of internal components using YAML, dependency control, and flow configuration.

Version management and multi-environment deployments (DEV → TEST → STAGING → PROD) with Git and Bitbucket.

Monitoring, troubleshooting, and incident resolution in distributed loads and large-scale processes.

Contribution to technical documentation, internal standards, and best practices within the data engineering area.

- Development of a Neural Network Model for Geospatial Point Classification and Influence Areas, using Python, Keras, and TensorFlow. Employing techniques such as convolutional layers and specific metrics for geospatial classification.

Responsibilities: Data Governance: National data governance project in collaboration with Vodafone Spain, ensuring data quality through efficient ETL processes and its integration into enterprise systems.

Geospatial Analysis: I use Geographic Information System (GIS) tools, such as GSA, Qgis to capture, store, and analyze geospatial data, facilitating location-based strategic decisions.

ETL and Data Quality: Development of ETL processes using Python, SQL, Putty to transform and load large volumes of data. Implementation of fuzzy matching and geospatial validation techniques to ensure data accuracy and consistency.

Databases: Working with MySQL and GIS tools, performing spatial analysis, data validation, and query optimization in relational databases.

Report Generation: Design and management of advanced reports in Power BI, providing clear and useful visualizations. Using Python to automate processes, data analysis, and insight generation.