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Azure Data Engineer
hace 4 meses
Buscamos
Azure Data Engineer para trabajar en modalidad Híbrida en una importante empresa transnacional de tecnología ubicada en la ciudad de Guadalajara Jalisco.
OFRECEMOS
Sueldo:
Abierto
Esquema de bonos por objetivos
Prestaciones de Ley
Esquema de trabajo; Híbrido (2 días de Home Office a la semana)
Zona de trabajo:
Guadalajara Zona Country Club, Av. Américas
REQUISITOS
Inglés Avanzado (Las entrevistas se realizarán en inglés)
Vivir en Guadalajara o estar dispuesto a reubicarse
EXPERIENCIA REQUERIDA
Exp.
como Data Engineer con Azure:
5 años +
Exp
diseñando y manteniendo DataWarehouse:
5 años +
Exp.
diseñando y manteniendo Data Lakes:
5 años +
Exp
con tecnologías Spark, Databricks:
5 años +
Exp.
con tecnologías Redshift o Snowflake:
5 años
Exp
construyendo Data Pipelines:
5 años +
Exp
con Linux:
5 años +
Job Description:
Cleans, prepares, and optimizes data for further analysis and modelling. Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to Data Pipeline (ie ELT) principles and business goals.
Roles and Responsibilities:
Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to ELT principles and business goals.
Solves complex data problems to deliver insights that helps business achieve its goals.
Creates data products for engineers, analysts, and data scientist team members to accelerate their productivity.
Engineer effective features for modelling in close collaboration with data scientists and businesses
Leads the evaluation, implementation and deployment of emerging tools and process for analytics data engineering to improve productivity and quality.
Fosters a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
Advises, consults, mentors, and coach other data and analytic professionals on data standards and practices.
Develops and delivers communication and education plans on analytic data engineering capabilities, standards, and processes.
Learns about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics as necessary to carry out role effectively.
