Cloud Data Engineer

at  Neotalent Conclusion

WHO ARE WE:

Neotalent Conclusion is one of the leading Iberian specialists providing services in Information Technology and Engineering services. As part of the Netherlands-based organization Conclusion, which has an ecosystem of over 25 companies and 3,600 employees, we are focused on increasing the technological capacity of our clients and the digital transformation of their application ecosystems.
We are talent specialists, attracting the best people and combining them with the needs of the most ambitious projects, at the right time. Our success comes from our investments in innovation, our focus on results, and, above all, the guarantee that our people will have happy and rewarding careers.
With over 25 years of solid experience, Neotalent Conclusion has established its presence in key locations, including Lisbon, Porto, and Madrid. The company currently has more than 950 professionals in the different areas in which it operates.
Neotalent, the responsive people.
Find out more about us at .

ROLE OVERVIEW:

We are looking for a Cloud Data Engineer to join a leading Iberian company in the energy sector, present in 30 countries, with a solid culture focused on innovation and digital transformation - offices in Lisbon (hybrid).

WHAT YOU WILL DO:

• Ensuring the management of applications and data in the cloud;
• Serverless Infrastructure: Collaborate in the design, development and serverless optimization of AWS for data pipelines;
• Adjust components for performance, scalability, security and data privacy.
• Smart Device Integration: Integrate smart devices using AWS IoT Core with secure protocols;
• Troubleshoot and ensure seamless device connectivity.
• External Data Integration: Extract, standardize and enrich data from external partners via APIs; Ensure robust error handling and data validation.
• Database Management: Administer SQL and NoSQL databases, ensuring configuration and optimization; Implement data retention, backups and collaborate with analysts.
• Data Pipeline Design: Design end-to-end data pipelines with quality checks and monitoring; Enhance pipelines to meet changing business needs.
• Data Lake Management: Architect scalable data lakes with partitioning, indexing and access controls; Maintain data lake integrity with data architects.