Timestamp Group aggregates several leading Portuguese IT solutions and services companies around the concepts of excellence and knowledge sharing. We are committed to technological leadership, based on the quality of our service and technological solutions, supported by continuous training and certification.
The project focuses on integrating and processing data from multiple energy markets, delivering high-quality, scalable, and reliable data products that enable business stakeholders to make data-driven decisions. Working within a modern cloud-based environment, you will contribute to the design, implementation, and optimization of production-ready data pipelines and data platforms.
Design, develop, and maintain scalable data pipelines and integration solutions using Python and Azure.
Stabilize and improve existing data processing implementations.
Implement new features and complete missing data pipelines.
Develop high-quality, maintainable, and well-tested production code following software engineering best practices.
Perform code, architecture, and design reviews, providing technical recommendations.
Troubleshoot complex production issues and perform root-cause analysis.
Contribute to CI/CD processes, release management, and DevOps practices for data workloads.
Collaborate with technical teams and business stakeholders to deliver reliable data products.
Document technical solutions, engineering decisions, and operational procedures.
4+ years of professional experience in Python development for production applications.
Strong background in Software Engineering or Backend Development, preferably in data-intensive or distributed systems.
Hands-on experience with Microsoft Azure, including:
Experience designing and operating scalable data pipelines.
Strong knowledge of data modelling (Dimensional Modelling, Domain-Driven Design, Event-Driven Architecture).
Experience with Git-based development workflows, CI/CD, Azure DevOps, and release management.
Proven experience troubleshooting complex production environments.
Apache Spark and Databricks.
Advanced SQL and relational database design.
Cloud security, IAM, and environment configuration.
Data quality, observability, governance, and lineage.
Data products, data contracts, SLAs/SLOs.
Enterprise-scale data platforms.
Schema evolution and metadata management.
Kafka, Azure Event Hub, or Spark Structured Streaming.
- Health insurance
- Flexibility in organizational routine
- Training and certifications
- Employee Support Program (in 5 areas, including psychology)
- Birthday and seniority gifts
- Monthly Happy Hour
- Benefits portal with attractive offers
