Senior Data Engineer – GCP

Are you an experienced Data Engineer passionate about building scalable data platforms, automating complex pipelines, and working at the intersection of Data Engineering, DevOps, and MLOps?

We’re looking for a technically strong and proactive Senior Data Engineer to join a growing data engineering environment. You’ll play a key role in designing, optimizing, and maintaining the infrastructure and pipelines that support data initiatives, Data Science projects, and analytical operations.

This is a great opportunity for someone who enjoys combining strong data engineering expertise with cloud, automation, and software engineering best practices, while helping bridge the gap between model development and scalable production environments.

🚀 What You’ll Be Doing:

• Design, develop, monitor, and automate robust data ingestion pipelines, covering both batch and streaming workloads.
• Build and maintain complex integrations with external APIs and third-party data sources, including application-level data extraction and web scraping scenarios.
• Design and organize scalable data storage solutions within Google BigQuery, following strong data modelling and Data Warehouse best practices.
• Structure and maintain clear data layers, from raw ingestion environments (Data Lake / Data Swamp) through to optimized Publish Layers for analytics and downstream consumption.
• Implement and improve CI/CD pipelines, ensuring reliable, automated, and repeatable deployments.
• Apply strong software engineering principles to build scalable, secure, maintainable, and well-documented solutions.
• Help structure and maintain modern repositories, including Monorepo environments, enabling efficient collaboration between Data Engineering and Data Science teams.
• Support the transition of Data Science solutions from development into production-ready environments.
• Contribute to the continuous improvement of the overall data platform, engineering standards, automation, and development practices.

What We’re Looking For:

Must-Have:

• Solid professional experience in Data Engineering or Software Engineering, particularly with large-scale data systems.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Advanced practical experience with Google BigQuery, including data modelling and Data Warehouse best practices.
• Strong understanding of modern data architectures, including Data Lakes, Lakehouse concepts, and layered data architectures.
• Experience designing and maintaining automated CI/CD pipelines, ideally using GitHub Actions or equivalent technologies.
• Good understanding of DevOps principles and automated deployment practices.
• Experience building and maintaining robust batch and/or streaming data pipelines.
• Professional proficiency in English (B2/C1), both written and spoken, for collaboration in an international technical environment.

⭐ Nice to Have:

• Hands-on experience with MLOps concepts and tools, including model lifecycle management, model API serving, and Feature Stores.
• Experience deploying solutions in Kubernetes or other container orchestration environments.
• Experience with Docker and Virtual Machines (VMs).
• Knowledge of observability and monitoring solutions such as Datadog or Grafana.
• Experience working in Agile/Scrum environments and using tools such as Jira.
• Previous experience supporting Data Science teams and helping move models or data products into production.

🛠 Tech Stack:

Cloud & Data: Google Cloud Platform (GCP), Google BigQuery

Data Architecture: Data Lake, Lakehouse, Data Warehouse, Raw Layers, Publish Layers

DevOps & Infrastructure: Docker, Kubernetes, Virtual Machines

CI/CD: GitHub Actions

Observability: Datadog, Grafana

Ways of Working: Agile, Scrum, Jira

Additional Areas: MLOps, APIs, Batch & Streaming Pipelines, Monorepo

Work Model:

This position follows a hybrid working model, with 2 days per week at the office.

If you’re looking for an opportunity where you can combine Data Engineering, GCP, DevOps, and MLOps while contributing to the evolution of a modern and scalable data platform, we’d love to hear from you.