Empresa: HAYS
Provincia: Madrid
Población: Madrid, Madrid
Descripción:
We are looking for a Senior Data Engineer . The successful candidate will leverage his/her experience and skills to onboard new data sources and service new destinations that enhance our products and service and increase our sales revenue. This position requires a creative, logical, and self-driven person with high standards for quality and attention to detail, capable of taking responsibility and accountability for actions and time management
Builds large-scale batch data pipelines
Leverages best practices in continuous integration and delivery
Drives optimization, testing and tooling to improve data quality
Interprets business requirements into technical requirements and executes
Enhances the ETL codebase for added efficiency and capacity.
Develops, recommends and implements process and procedure changes to systematically improve data integrity.
Analyzes data sets, builds visualizations and develops dashboards to inform internal and external clients.
Designs, creates and manages processes to prepare both static and streaming data for use in machine learning algorithms
We work as a distributed engineering team using agile methodologies such as Kanban/Scrum.
Skills and Requirements Must Have Skills:
Has 3+ years of professional experience in ETL and/or other “Big Data” processes including modelling and data architectures
Understands Big Data stack including:
MapReduce
Hadoop
Spark
Hive
Is familiarity with relational and hierarchical database development
Has strong written and verbal presentation skills and is capable of communicating technology benefits to business problems
Possesses knowledge of data warehousing, data preparation, analytics, reporting and dashboarding for data at terabyte scale using platforms such as Kylin
Tecnologías: ETL, MapReduce, Hadoop, Spark, Hive,
Tipo de Contrato:
Indefinido
Salario: Sin especificar
Experiencia: 3 años
Funciones: Big Data
Descubre más: https://www.tecnoempleo.com/data-engineer-american-company-madrid/etl-mapreduce-hadoop-spark-hive/rf-d41dz8cd948f0h0b20y4
