Azure Data Engineer

Sobre Mindtech

Mindtech es tu puerta de entrada a proyectos tecnológicos emocionantes y con impacto. Nos especializamos en staff augmentation y outsourcing de software de punta a punta, conectando el talento de América Latina con oportunidades a nivel global. Nuestro enfoque ágil garantiza a nuestros clientes un servicio excepcional y soluciones innovadoras.

Sobre el puesto

An Azure Data Engineer would focus on designing, building, and maintaining data pipelines, warehouses, and data lakes using Azure services. This includes technologies like Azure Data Factory, Synapse Analytics, and Data Lake, along with data processing and visualization tools like Power BI. The role involves extracting, transforming, and loading (ETL) data from various sources, ensuring data quality, and collaborating with other teams to support business intelligence and AI/ML initiatives.

Requisitos

Azure Expertise: Strong knowledge and experience with Azure services, particularly Azure Data Factory, Synapse Analytics, and Data Lake Storage.

Data Engineering Fundamentals: Experience with data warehousing, ETL processes, data modeling, and data quality practices.

SQL: Proficient in SQL for data manipulation, querying, and data modeling.

Programming Skills: Familiarity with at least one programming language (e.g., Python, Scala) for scripting and automation.

Data Visualization Tools: Experience with data visualization tools like Power BI or Tableau.

Big Data Technologies: Knowledge of big data technologies and frameworks (e.g., Spark, Hadoop) would be beneficial.

Responsabilidades

Data Pipeline Design and Development: Design, build, and maintain robust and scalable data pipelines using Azure Data Factory and other Azure services to move data between different systems and storage locations.

Data Warehousing and Data Lake Management: Develop and manage data warehouses (using Synapse Analytics) and data lakes (using Azure Data Lake Storage) to store and manage large datasets for analytics and reporting purposes.

ETL Processes: Extract, transform, and load data from various sources (e.g., relational databases, APIs, cloud services) into the data warehouse or data lake using Azure Data Factory.

Data Quality and Governance: Implement data quality checks, validation, and cleaning processes to ensure data accuracy, consistency, and reliability.

SQL and Data Modeling: Apply strong SQL skills and data modeling knowledge to design and optimize data structures for efficient data retrieval and storage.

Data Visualization and Reporting: Develop interactive dashboards and reports using Power BI or other data visualization tools to present insights derived from data.

Ofrecemos

• Trabajo Híbido

• Contrato a Long Term

• Salario en USD

• Programa de referidos

• Desarrollo profesional en entornos dinámicos y globales