AI Data Engineer
Factbird
Software Engineering, Data Science
Copenhagen, Denmark
Posted on Jan 15, 2026
At Factbird, we’re building technology that helps people on the factory floor work smarter. By bringing together hardware, firmware, cloud, and AI, we turn complex production data into insights that create real, everyday impact.
As we continue to grow, we’re looking for an AI Data Engineer who cares deeply about building reliable, thoughtful data foundations that power meaningful AI experiences. In this role, you’ll help transform raw data into production-ready intelligence — supporting AI features like real-time insights, predictive analytics, and AI-driven services that our customers truly rely on.
You’ll be part of a collaborative, supportive team, working at the heart of our AI efforts to ensure data is fresh, trustworthy, and ready to make a difference in real-world production environments.
About the role
As an AI Data Engineer, you will bridge the gap between raw data and production-grade AI features. You will architect and maintain the high-scale data pipelines that power our SaaS platform’s intelligent services—including real-time recommendations, generative AI agents, and predictive analytics. Your focus is on reliability, scalability, and ensuring that our AI models have access to high-quality, fresh data in a production environment.
- Department
- Cloud
- Employment Type
- Full Time
- Location
- Copenhagen
- Workplace type
- Onsite
Key Responsibilities
- Production Pipeline Architecture: Design and build robust ETL/ELT pipelines to ingest data from SaaS APIs, event streams, and relational databases.
- AI Infrastructure & Feature Stores: Implement and manage feature stores to provide low-latency data to production machine learning models.
- Generative AI Integration: Integrate and optimize data flows for LLM-powered features.
- Real-time Processing: Build and scale streaming pipelines to support instant AI-driven user experiences.
- Data Governance & Quality: Enforce data contracts and implement automated testing to ensure model inputs remain accurate and secure.
- Cloud Cost Optimization: Monitor and compute resources to maintain profitable SaaS margins.
- Cross-Functional Collaboration: Partner with ML Engineer and AI PM to productionize research models and ensure seamless model retraining cycles.
About you
- Experience: 4–7 years in data engineering, with at least 2 years focused on production-grade AI/ML pipelines.
- Programming: Mastery of Python (specifically for data manipulation) and advanced SQL.
- Cloud Platforms: Expert knowledge of AWS or Azure ecosystems, including serverless architectures and containerization (Docker, Kubernetes).
- Modern Data Stack: Proficiency with dbt, Spark, and cloud-native data warehouses like Snowflake or Databricks.
- AI Fundamentals: Solid understanding of the ML lifecycle, model versioning, and the specific data requirements of NLP and LLM applications.
- Soft Skills: Strong trade-off reasoning and the ability to communicate technical data flows to non-technical product stakeholders.
Preferred Qualifications
- Experience with MLOps frameworks (e.g., MLFlow, SageMaker).
- Familiarity with data privacy regulations (GDPR, CCPA) as they apply to AI model training.
- Relevant certifications (e.g., AWS Certified Data Engineer, Google Professional Data Engineer).
Why Factbird?
People are at the heart of everything we build. We believe great products come from empowered teams — and we work hard to create an environment where you can do your best work and have space for life beyond it.
Here’s what you can look forward to:
- Flexible working hours: We trust you to manage your time. Life isn’t one-size-fits-all, and neither is work.
- Competitive salary: We offer compensation that reflects your skills, experience, and impact.
- Internet reimbursement: Stay connected and productive, wherever you choose to work from.
- Thoughtful, human onboarding: We’ll support you step by step, giving you the context, tools, and guidance you need to feel confident from day one.
- A career path that grows with you: Through bi-yearly Individual Development Plan conversations, we’ll work together to shape a career journey that fits your ambitions.
- Company-wide kickoffs & team days: We regularly come together across teams and regions to connect, celebrate, and align on what’s next.
- A global, inclusive culture: We’re proud of our diverse backgrounds and perspectives — and we actively celebrate them in how we work and collaborate.
We’d love to hear from you
If this role feels like a match, we’d be excited to hear from you and explore how you could help shape the future of data collection and production monitoring at Factbird.
And if someone in your network comes to mind who might be a great fit — feel free to share this opportunity with them.
Have questions? You can always reach out at [email protected]💛
At Factbird, we believe that great work starts with people feeling respected, valued, and included. We are proud to be an equal opportunity employer and are committed to building a workplace where everyone has the opportunity to thrive.
All employment decisions at Factbird are made based on business needs, role requirements, and individual qualifications, without discrimination based on gender, gender identity or expression, age, disability, marital or family status, nationality, ethnic or social origin, religion or belief, sexual orientation, or any other characteristic protected under applicable European and local employment laws.
We celebrate diversity in all its forms and believe that different backgrounds, perspectives, and experiences make our teams stronger and our work better. We warmly encourage all qualified candidates to apply and to bring their whole selves to Factbird.
About Factbird
Great people make great things happen
Factbird is on a mission to make manufacturing more efficient. We build intuitive tools that give frontline teams the insights they need to reduce waste, improve processes, and stay ahead. Since 2016, we’ve helped manufacturers worldwide drive real change. Now, we’re searching for great people to help us do even more.
Our Hiring Process
Stage 1:
Applied
Stage 2:
Review
Stage 3:
First Interview
Stage 4:
Second Interview
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