Senior/Lead GCP Data Engineer

Role Summary

As a GCP Data Engineer, you will design, build, and optimize cloud-native data platforms on Google Cloud Platform. Working closely with data engineers, data scientists, analysts, and software engineers across international teams, you will create robust data pipelines, support AI and machine learning initiatives, and ensure reliable access to high-quality data at scale. You will contribute to the development of modern data architectures that power advanced analytics, automation, and intelligent customer experiences while applying software engineering best practices throughout the development lifecycle.

About the Team

You will join a globally connected team focused on delivering scalable data solutions across ING. The team is passionate about innovation, collaboration, and continuous learning, leveraging cloud-native technologies to create reliable and future-ready data products. Together, we enable business value through data, analytics, and emerging AI capabilities.

About You

We hire smart people for their potential. Our biggest expectation is that you'll stay curious, keep learning, and take on responsibility. In return, we'll back you to develop into an even more awesome version of yourself. We're looking for someone who brings:

Minimum Qualifications

• Bachelor’s degree or equivalent practical experience.
• Excellent communication skills and the ability to collaborate effectively within globally distributed teams.
• Hands‑on experience building complex data pipelines using technologies such as PySpark and Airflow.
• Strong programming skills in Python and SQL.
• Experience designing data models and working with relational or distributed database systems.
• Understanding of software engineering best practices, including CI/CD and testing approaches.
• Hands‑on experience with Google Cloud Platform services such as BigQuery, Cloud Storage, and Cloud Composer.

Preferred Qualifications

• A curious mindset and passion for continuous improvement and knowledge sharing.
• Experience with infrastructure provisioning and deployment automation tools.
• Familiarity with monitoring and observability platforms such as the ELK Stack.
• Knowledge of MLOps architecture and operational practices.
• Experience in data transformation and large‑scale data processing.
• Exposure to AI‑powered solutions, including Agentic AI systems, Chatbots, or Voicebots.
• Experience designing and operating data or ML workflows on GCP, including services such as Vertex AI and Dialogflow.

Roles and Responsibilities

• Design, develop, and maintain scalable cloud-native data pipelines on Google Cloud Platform.
• Build and optimize data ingestion, transformation, and storage solutions for large-scale datasets.
• Develop reliable and efficient data models supporting analytics, reporting, and AI use cases.
• Collaborate with cross‑functional teams to understand business requirements and translate them into technical solutions.
• Implement software engineering best practices, including automated testing and CI/CD processes.
• Monitor and improve data platform performance, reliability, and observability.
• Support AI, machine learning, and MLOps initiatives by delivering trusted and accessible data assets.
• Contribute to continuous improvement, knowledge sharing, and engineering excellence within the team.

What We Offer

• Be Yourself, Be an ING’er
• Leave: 14 days of welcome leave, even in your first year.
• Career opportunities: Self‑driven career paths and growth opportunities.
• Personalgrowth: Challenging work and continuous development opportunities.
• Dynamic environment: Informal, vibrant, and collaborative working culture.
• Innovation culture: Opportunity to contribute ideas and work with PACE methodology.
• Global exposure: Participation in international projects and communities.
• Health care: Comprehensive private health insurance for you and your family.
• Private pension plan
• Meal card
• Transportation allowance
• MultiSport membership
• English language development support