This is us

At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.

This is the job

In Latin America, we are looking for a Senior/Principal Big Data Engineer to join one of our international projects. You will be responsible for designing, implementing, and maintaining robust big data solutions, mainly using Cloudera, and potentially with AWS, Azure, or GCP. Your focus will be on large-scale data processing, architecture implementation (Lambda/Kappa), and orchestrating complex pipelines using modern technologies like Spark, Docker/Kubernetes, and orchestration tools like Airflow or Jenkins.

This is you

• 5+ years of experience in implementing and managing Big Data solutions (Cloudera required, AWS/Azure/GCP is a plus).
• 5+ years of experience developing in Python or Scala, and scripting with Shell.
• Strong knowledge of structured query languages (SQL, HQL, TSQL, PL/SQL, etc.).
• Proven experience in Lambda architecture (4+ years) and Kappa architecture (3+ years).
• Familiarity with the design and implementation of dimensional models (3+ years).
• Solid understanding of distributed storage and processing, and real-time data analysis.
• Experience managing distributed processing engines, especially Apache Spark (4+ years).
• Proficient in using orchestration tools like Airflow, Jenkins, or Oozie (2+ years).
• Hands-on experience with Docker and/or Kubernetes (2+ years).
• Strong understanding of data ingestion, cleansing, validation, and integration processes.
• Excellent communication and collaboration skills.
• Spanish: Fluent (mandatory).

This is your role

• Implement and administer Big Data solutions, primarily with Cloudera.
• Develop high-performance data pipelines using Python or Scala.
• Work with Spark for distributed data processing.
• Design and build Lambda and Kappa architectures.
• Integrate structured/unstructured data into centralized repositories.
• Design and implement dimensional models for Data Warehouses and Data Marts.
• Manage orchestration of data flows using tools like Airflow, Jenkins, or Oozie.
• Deploy and manage containers with Docker and/or Kubernetes.
• Define and maintain standards for data flow modeling, monitoring, and validation.