Data Context Engineer (m/f/d)
Siemens Amadora, Portugal
Automation Machinery Manufacturing · 10,001+ employees
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About the role
Build and maintain governed data transformation pipelines, semantic models, and knowledge graph structures that support reliable analytics and AI applications. Connect enterprise data platforms with AI retrieval systems, establish data quality and governance workflows, and collaborate with engineering, business, and AI teams to standardize metrics and taxonomies.
What they look for
Requirements
A degree in Computer Science, Data Science, Information Systems, Software Engineering, or a related technical field is requested, along with proven data and analytics engineering experience using Snowflake, dbt, AWS, SQL, and Python. Candidates should have Power BI and semantic modeling experience, familiarity with data CI/CD and modern AI/ML concepts, and strong communication skills with fluency in English; industrial, IoT, or PLM experience is a plus.
Benefits
Full description
Siemens Global Business Services (GBS) enables Siemens units worldwide and external customers to accelerate their business transformation into a sustainable and digital future.
Our portfolio comprises services driven by expertise and the latest technology – with a strong focus on innovation and digitalization in areas like Finances, Business Administration, Human Resources, Procurement, Sales and After-Sales.
In our GBS Western Europe and Africa Hub we are already more than 1500 connected people, from over 50 different nationalities spread across 14 countries. If you value diversity and innovation, you’ll feel right at home here!
Discover our purpose, culture, and what makes GBS unique!
Are you ready to be part of the change? Come join us! ⭐
The GBS Digital Solutions (DS) Enterprise Architecture team, part of Governance, Cybersecurity & Integration (GCI), sets the architecture direction for GBS. We enable, facilitate and govern, working with the business lines and delivery teams rather than apart from them. Our goal is simple: decide faster, and apply the right technology to each use case.
What role will you play?
- Build and scale enterprise-grade data transformation pipelines and semantic models to deliver reliable, governed analytical datasets.
- Design, implement, and maintain semantic layers and knowledge graph structures that translate complex industrial domain concepts into machine-interpretable schemas for AI models and business stakeholders.
- Bridge traditional business intelligence and modern AI context retrieval, ensuring seamless data flow between core analytics platforms and AI agent frameworks.
- Develop automated data pipelines, schema tests, and governance workflows to ensure data quality, semantic integrity, and consistency across both BI reports and AI applications.
- Collaborate with data engineering and cloud infrastructure teams to architect performant, cost-effective data flows connecting operational systems, data lakes, and AI services.
- Design context-retrieval mechanisms and semantic overlays that ground Large Language Models (LLMs) and predictive models in validated enterprise and product lifecycle data.
- Work closely with domain specialists, analytics engineers, and AI practitioners to standardize business metrics and taxonomies, accelerating the enterprise transition toward AI-augmented operations.
What do you bring?
- Degree in Computer Science, Data Science, Information Systems, Software Engineering, or a related technical field.
- Proven track record in data engineering and analytics engineering, with deep hands-on expertise in Snowflake, dbt, and AWS cloud data services.
- Strong proficiency in advanced SQL and Python for data transformation, automation, and API integration.
- Hands-on experience developing enterprise semantic models and interactive dashboards in Power BI, with a clear understanding of DAX, data modeling, and enterprise reporting architectures.
- Working knowledge of modern AI/ML concepts, including Retrieval-Augmented Generation (RAG), vector databases, semantic search, or knowledge graphs (such as RDF, OWL, Neo4j, or graph traversal techniques) (nice-to-have).
- Demonstrated experience in data modeling methodologies (dimensional modeling, semantic layers, data vault) and CI/CD best practices for data (version control with Git, automated testing with dbt).
- Experience or strong interest in industrial data domains, IoT telemetry, or Product Lifecycle Management (PLM) systems is a plus.
- Ability to act as a bridge between traditional data analytics teams and cutting-edge AI development teams.
- Excellent communication skills with fluency in English.
What We Offer:
- Belong & Innovate: Work in diverse teams where every idea matters and innovation grows through collaboration and trust.
- Flexibility that Works: Hybrid model, flexible hours, and a home office budget — because balance fuels performance.
- Health & Well-being: Comprehensive health insurance, mental health support, and active sports communities to keep you feeling your best.
- Grow Without Limits: Access world-class learning platforms, mentoring, and continuous development opportunities.
- Purpose & Perks: Contribute to sustainability and volunteer initiatives, enjoy partner discounts, and take advantage of our convenient shuttle service.
Please attach your CV in English to your application.
Create a better #TomorrowWithUs #Siemens 🚀
Siemens is deeply committed to fostering a diverse and inclusive environment. We are proud to be an equal opportunity employer and strongly encourage applications from a wide array of talented individuals!
Job ID
525481
Posted since
16-Oct-2026
Organization
Global Business Services
Field of work
Information Technology
Company
Siemens S.A.
Experience level
Experienced Professional
Job type
Full-time
Work mode
Hybrid (Remote/Office)
Employment type
Permanent
Location(s)
• Amadora - Lisboa - Portugal
