Big Data Engineer - Cloudera

Babel, the great way to achieve the success.

Do you want to be part of an expanding, committed, and innovative team that makes history every day? At Babel, we accompany you on your path to success. We believe in the talent of people and we want to empower it by offering you a great working environment based on collaboration and solidarity.

Working at Babel is much more than working at a company; it is joining a team of people with a shared mission and a company model centered on values.

And we do this by promoting diversity, equity, and inclusion, guaranteeing equal opportunities to all candidates, in an environment free of any type of discrimination.

Additionally,

• We bet on work-life flexibility. (Point-based vacation system, remote work, and flexibility).

• We invest in the training of our Babelievers.

• We invest in your physical and emotional health. (Private Medical Insurance/ Life insurance, personal trainer, and wellbeing program).

• We also invest in your free time (Nature activities, sports championships, streaming platform subscription (e.g., Netflix))

• We participate in the growth of the company and recognize the participation of each person (Benefits Bonus).

• We focus on working with the latest technologies and innovative projects, but above all, we accompany digital transformation and bring technology closer to society.

Do you accept the challenge? We are waiting for you!

We are looking for a Data Engineer with experience in Big Data and Data Lake environments, to participate in the design, development, and optimization of large-scale data processing solutions.

The role combines data engineering, integration of multiple sources, and pipeline development, working with Cloudera and SQL ecosystem technologies in cloud environments.

• Design and develop data pipelines and transformation processes in Data Lake environments.
• Implement ingestion, integration, and data preparation processes from different sources.
• Design data models and datasets for analytical exploitation.
• Optimize performance, scalability, and resource consumption in Big Data processes.
• Manage dependencies and process orchestration.
• Participate in testing, deployment, and production support.
• Document solutions and apply data engineering best practices.