Data Warehouse Engineer
Builds and optimizes the enterprise data warehouse for the Stadler rail group's Digital Labs: designing ETL pipelines, integrating multiple ERP and database sources, tuning performance, and automating deployments. Core stack is Microsoft SQL Server, SSIS/SSRS/SSAS and T-SQL, plus Python and PowerShell for automation.
- Compensation
- Not disclosed
- Location
- Portugal
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Academic background in Engineering or similar (Software, Electronics, Physics, Mathematics)
- 5+ years of professional experience in data warehouse architecture and automation (Microsoft SQL Server, SSIS, T-SQL)
- Proven skills in DWH design, development, and optimization using Microsoft SQL Server, SSIS, SSRS, SSAS and T-SQL
- Deep knowledge of ETL pipeline design, optimization, and troubleshooting
- Proven skills in performance tuning, scalability, and maintainability of DWH systems
- Experience with multiple ERP systems (e.g., SAP, Abacus, INFOR) and diverse databases (SQL Server, Oracle, MariaDB, PostgreSQL, Progress)
- Strong scripting and automation skills (Python for data workflows, PowerShell for deployment and monitoring)
- Validate compliance with DWH standards, data governance, and architectural best practices
- Expertise in integration of heterogeneous data sources and adapting legacy systems to modern architectures
- Experience in deployment automation and environment configuration across development, test and production
- Focus on data validation, anomaly detection, and error handling
- Ability to produce technical documentation and foster knowledge sharing
- Able to collaborate with developers and review technical solutions for quality and consistency
Nice to have
- Passionate and driven, curious, willing to share knowledge and learn from others regardless of background, tenure or seniority
- Awareness of AI trends (including agentic AI) with curiosity to explore how they can enhance products, processes, or ways of working
- Learning mindset toward emerging technologies and openness to experiment and upskill in an AI-enabled environment
Full description
The future of rail isn't just about movement, it's about intelligence, security, and connection. We unite rail expertise with digital innovation to create smarter, safer, and more sustainable transportation solutions. Technology here speaks with purpose: accelerating digitalization, embedding cybersecurity, and shaping the next era of rail.
Behind every breakthrough are people, their talent, creativity, and drive to push boundaries. Together, we're building confidence, resilience, and a new standard for connected mobility powered by innovation.
This position is for Stadler Digital Labs, a joint venture between Stadler Rail and Critical Software serving as the digital competence center for the Stadler Group.
Check-out the website: https://stadlerdigitallabs.com
Which brings us to you, the person with:
- Academic background in Engineering or similar (Software, Electronics, Physics, Mathematics, etc.).
- At least 5+ years of relevant professional experience in data warehouse architecture and automation (Microsoft SQL Server, SSIS, T-SQL).
- Proven skills in data warehouse (DWH) design, development, and optimization using Microsoft SQL Server, SSIS, SSRS, SSAS and T-SQL.
- Deep knowledge of ETL pipeline design, optimization, and troubleshooting.
- Proven skills in Performance tuning, scalability, and maintainability of DWH systems.
- Experience with multiple ERP systems (e.g., SAP, Abacus, INFOR) and diverse databases (SQL Server, Oracle, MariaDB, PostgreSQL, Progress).
- Strong skills in scripting and automation (Python for data workflows, PowerShell for deployment and monitoring).
- Validate compliance with DWH standards, data governance, and architectural best practices.
- Expertise in integration of heterogeneous data sources and adapting legacy systems to more recent architectures.
- Experience in deployment automation and environments configuration (across development, test and production).
- Focus on data validation, anomaly detection, and error handling.
- Ability to produce technical documentation and foster knowledge sharing within and across teams.
- Able to collaborate with developers and review technical solutions for quality and consistency.
- Passionate and driven, curious and willing to share your knowledge, but also learn with others - regardless of their background, tenure or seniority.
- Demonstrates awareness of AI trends (including agentic AI), with curiosity and motivation to explore how they can enhance products, processes, or ways of working;