Cloud Data Engineer

buscojobs España; Salamanca; Presencial; EUR 40.000 - 70.000; Jornada completa

Descripción de la vacante

A leading consulting firm is seeking a Cloud Platform and Data Engineer to join their international team. This role involves working with AWS cloud engineering, data engineering tools, and programming languages like Python and Java. You will be responsible for project planning, developing data pipelines, and ensuring data integrity. This position offers an opportunity to thrive in a dynamic environment and contribute to impactful projects.

Formación

• Proven experience in AWS cloud engineering and platform engineering.
• Strong experience with data engineering tools and frameworks.
• Proficiency in programming languages such as Python, Java, or Scala.

Responsabilidades

• Plan the kickoff and follow up on projects.
• Ensure data integrity and work with AWS APIs.
• Develop pipelines and construct ETLs.

Conocimientos

AWS cloud engineering

data engineering tools

Python

Java

Scala

CI/CD pipelines

DevOps best practices

ETL construction

data integrity

AWS APIs

Docker

Kubernetes

Databricks

Descripción del empleo

Take your career to the next level with Amaris Consulting as a Cloud Platform and Data Engineer . Become part of an international team, thrive in a global group with €800M turnover and 1,000+ clients worldwide, and an agile environment by planning the kickoff and follow up on projects. Join Amaris Consulting, where you can develop your potential and make a difference within the company.

• Proven experience in AWS cloud engineering and platform engineering.
• Strong experience with data engineering tools and frameworks.
• Proficiency in programming languages such as Python, Java, or Scala.
• Familiarity with CI / CD pipelines and DevOps best practices.
• Experience constructing ETLs, developing pipelines, ensuring data integrity , and working with AWS APIs .
• Familiarity with containerization technologies like Docker and Kubernetes .
• Experience with Databricks for machine learning and pipelines.