With over 14 years of experience in the banking sector in the IT Area, I am a Data Engineer completing a Master in Big Data & Business Analytics with experience in Cloud environments such as AWS and Azure. My specialty is the design, development, documentation, and testing of ingestion solutions for data processing and analysis on Big Data platforms such as Cloudera, Datio, and Databricks, using tools such as PySpark, Scala, Python, Hive, Impala, HBase, Kudu, Kafka, Oozie, Airflow and SQL. I have worked with distributed file systems such as HDFS and with relational databases: SQL Server, Sybase, Oracle, MySQL, Postgres, and non-relational databases: DynamoDB, additionally with Datawarehouse environments such as Teradata, Redshift, and Snowflake.My passion is to work in an environment where I can apply my skills and knowledge to develop innovative solutions that add value to the business and users. I especially enjoy teamwork and collaboration in implementing agile methodologies such as Scrum and Kanban, which allow for delivering high-quality results within tight deadlines. My goal is to contribute to the constant growth of the team, fostering a collaborative work environment oriented toward continuous learning. My last project was in Santander Bank Mexico, where I participated in the design and development of new data ingestion requirements for the entity's Data Lake, using the Cloudera environment: Scala, PySpark, Python, Hive, Impala, HBase, Ozzie, and HDFS in the Hadoop ecosystem. Additionally, I analyzed and managed business intelligence requirements related to all core banking operations (Power BI), ensuring the alignment of solutions with business needs and the optimization of processes.Skills and knowledge:• Big Data Developer• Apache Spark and Hadoop (HDFS, Hive, Impala, HBase, Kudu, Kafka, HBase, Ozzie)• ETL Developer• Machine Learning (Python, RapidMiner)• PySpark• Databricks• Implementation of BI Models (Power BI, Tableau)• Databases (SQL and NoSQL)• DataWarehouse (TERADATA, Redshift, Snowflake)• AWS (Lake Formation, Glue, S3, IAM, EMR, Athena, ...)• Azure (Data Fabric)• Web Scraping with Python• Version control with GitHub• Implementation of DQ data quality models• Management of incidents• Agile Methodologies (Scrum, Kanban)• Process Planning in Control-M
