Data Platform Solution Architect Automation & Innovation Department

• Senior-level experience in data engineering, data platform engineering or cloud solution architecture.
• Proven hands-on experience designing and implementing production data solutions on Google Cloud Platform.
• Strong practical knowledge of BigQuery, Cloud Storage, Cloud Run i Cloud SQL and Cloud Composer or Apache Airflow.
• Experience with data processing technologies such as Dataflow, Apache Beam, Dataproc or Apache Spark.
• Strong programming skills in Python and SQL.
• Hands-on experience with Terraform and Infrastructure as Code.
• Experience building and maintaining CI/CD pipelines for data and infrastructure deployments.
• Strong understanding of batch and event-driven data ingestion patterns.
• Experience designing data models, transformation pipelines and orchestration workflows.
• Understanding of GCP security, IAM, service accounts, networking and secrets management.
• Experience with monitoring, logging, alerting and troubleshooting production data pipelines.
• Ability to translate business requirements into technical architecture and working implementations.
• Ability to assess technical trade-offs related to scalability, performance, maintainability and cost.
• Strong communication skills and the ability to work with both technical and business stakeholders.

Nice to have

• Experience with data governance, metadata management, lineage or data quality solutions.
• Knowledge of containerisation and Kubernetes, particularly Docker and GKE.
• Experience creating reusable Terraform modules and platform engineering standards.
• Understanding of DataOps, FinOps and cloud observability practices.
• GCP Professional Data Engineer, Professional Cloud Architect or Terraform certification.

We are looking for a hands-on Data Platform Solution Architect who will design and implement data use cases on our GCP data platform.

You will work with business and technical teams to understand use case requirements, translate them into scalable data solutions and take an active role in their implementation. This role combines solution architecture, technical leadership and hands-on data engineering.

,[Translate business use cases into scalable technical solutions on GCP., Design and implement end-to-end data pipelines covering ingestion, storage, transformation and consumption., Select appropriate GCP services, integration patterns and data processing approaches for each use case., Build and configure the infrastructure required to deploy use cases on the data platform., Develop reusable components and patterns instead of isolated, use case-specific solutions., Implement Infrastructure as Code and automated deployment pipelines., Ensure solutions meet security, data governance, reliability, performance and cost requirements., Troubleshoot complex technical issues across infrastructure and data pipelines., Provide technical direction and support other engineers in architecture and implementation decisions., Identify recurring use case requirements and translate them into reusable platform capabilities., Proactively contribute to the technical roadmap and evolution of the data platform.] Requirements: Data engineering, Cloud, Google Cloud Platform, BigQuery, Storage, Cloud SQL, Cloud Composer, Apache Airflow, Apache Beam, Apache Spark, Python, Terraform, SQL, Infrastructure as Code, CI/CD Pipelines, Data models, GCP, Security, IAM, Networking, Data pipelines, Communication skills, Kubernetes, Docker