Data Engineer

Collaborating with cross-functional product teams, you will help turn complex business needs into innovative, data-driven solutions.

Responsibilities:

• Develop and maintain efficient, scalable data pipelines using Google Cloud Platform (GCP).
• Design and implement solutions leveraging core GCP services such as BigQuery, DataProc, and Pub/Sub.
• Ensure effective data modeling and storage using columnar NoSQL databases like BigQuery and MongoDB.
• Collaborate with product teams to deliver solutions tailored to business requirements.
• Work with event-driven architectures, using tools like Apache Kafka and GCP’s streaming capabilities.
• Optimize costs and efficiency in cloud environments (FinOps).
• Ensure stability, performance, and continuity of GCP-based BI and Big Data tools.

• experience

• skills
• A Bachelor’s degree (or equivalent work experience) in Computer Science, Software Engineering, or a related field.
• At least 4 years of hands-on experience building production-grade data systems, with a focus on Google Cloud Platform.
• Expertise in:
• GCP Services: BigQuery, DataProc, Pub/Sub, and Cloud Storage.
• Data processing tools: Apache Spark, especially on DataProc.
• CI/CD practices: Using GIT and GITactions for deployment pipelines.
• Data modeling and warehousing in a cloud environment.
• Event streaming tools such as Apache Kafka or GCP Pub/Sub.
• Infrastructure-as-code tools like Terraform and containerization using Docker.
• Knowledge of programming languages such as Python, Scala, or Java.
• Familiarity with the Hadoop ecosystem and related tools.
• Strong analytical and problem-solving skills, with a solid understanding of algorithms and data structures.
• Experience with data management tools (e.g., Collibra) is a plus.

Nice to have:

• Experience with Spark Structured Streaming and Kafka Connect.
• Affinity with Machine Learning or Operations Research concepts.
• Knowledge of Agile methodologies.

• qualifications

WO,HBO