You will work within an innovative, data-driven organization where cloud, data, and AI play an important role in further digital development. You will be responsible for designing, building, and optimizing scalable data and AI solutions within Google Cloud Platform (GCP). You will work at the intersection of data engineering, cloud engineering, and AI, ensuring that data is reliably, securely, and efficiently made available for analytical applications, machine learning, and generative AI.
You will collaborate closely with data scientists, software engineers, cloud engineers, and business stakeholders.
What you will do.
- Design, build, and maintain scalable data pipelines and data platforms within Google Cloud Platform (GCP)
- Develop reliable data solutions for analytics, machine learning, and AI applications
- Build and optimize data pipelines for batch and streaming data
- Unlock, transform, and model large amounts of structured and unstructured data
- Integrate AI and machine learning solutions within existing data and cloud architectures
- Develop production-ready solutions around generative AI, LLMs, and/or machine learning
- Automate deployment and infrastructure using CI/CD and Infrastructure-as-Code
- Monitor performance, scalability, security, data quality, and reliability of the platform
- Collaborate with data scientists and AI engineers to bring models and AI applications to production
- Actively contribute to technical standards, architectural choices, and further professionalization of the data and AI platform
Profile
You combine strong data engineering skills with knowledge of modern cloud and AI technologies. You have experience building production-ready data solutions and understand how a scalable cloud platform is set up. You are technically strong, think in terms of quality and automation, and find it interesting to translate new developments in data, machine learning, and generative AI into practical solutions.
What they ask
- Minimum 3 years of relevant experience in data engineering, cloud engineering, and/or AI engineering
- Strong hands-on experience with Google Cloud Platform (GCP)
- Experience with GCP services such as BigQuery, Cloud Storage, Pub/Sub, Dataflow, and/or Dataproc
- Excellent knowledge of Python and SQL
- Experience designing and developing ETL/ELT pipelines and modern data architectures
- Experience with CI/CD, Git, and automated deployments
- Knowledge of data modeling, data quality, and scalable data processing
- Experience developing and managing production-ready cloud solutions
Nice-to-haves.
- Experience with Vertex AI and other AI/ML services within Google Cloud
- Experience with generative AI, Large Language Models (LLMs), and RAG solutions
- Experience with Apache Beam, Spark, or other distributed processing frameworks
- Knowledge of orchestration tooling such as Airflow / Cloud Composer
- Experience with Infrastructure-as-Code, for example Terraform
- Experience with Docker and Kubernetes / GKE
- Experience with dbt
- Knowledge of MLOps, model deployment, and model monitoring
- Knowledge of the aviation industry is a plus
How to apply
View the full assignment text and application details once your tailored application is ready.
Order a tailored application to view the full assignment and application details.
More context, less searching.
You get enough context to judge whether this job is relevant. The full brief, client details and next steps stay available inside the app.