Data Context Engineer (m/f/d)

Siemens AG; Amadora; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Hybrid model

Home office budget

Health insurance

Learning & development

Shuttle service

Job summary

Siemens AG's Global Business Services in Portugal seeks an analytics engineer to build enterprise data pipelines, semantic models, and knowledge graphs that power AI and business insights.

You will collaborate with data engineering, cloud teams, and domain experts to enable CI/CD for data, ensure quality, and deliver scalable BI and AI-ready datasets across the organization.

Qualifications

• Degree in Computer Science, Data Science, or related field.
• Hands-on data engineering and analytics experience with Snowflake, dbt, and AWS.
• Strong SQL and Python skills for data transformation and automation.

Responsibilities

• Build and scale data pipelines and semantic models for analytics datasets.
• Design semantic layers and knowledge graphs for AI and business users.
• Bridge BI and AI contexts, ensuring data flows between analytics and AI apps.
• Develop automated pipelines, tests, and governance workflows for data quality.
• Collaborate with data engineering and cloud teams to optimize data flows.

Skills

SQL

Python

English fluency

Data modeling

CI/CD for data

AI/ML concepts

Education

Bachelor's or Master's in CS/Data Science/IS/SE

Tools

Snowflake

dbt

AWS

Power BI

DAX

Neo4j

Job 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!

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.

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!