GCP Data Engineer needed at PBT Group

• Our team is seeking an experienced Google Cloud Platform (GCP) Data Engineer with a passion for building and optimising data pipelines, architectures, and data sets on GCP. This role involves collaborating closely with data analysts, data scientists, and other stakeholders to ensure high-quality data availability for advanced analytics and machine learning initiatives.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL processes on GCP to support a variety of data applications, including analytics, reporting, and machine learning.
• Implement and manage data warehouses and data lakes using GCP services such as BigQuery, Cloud Storage, Cloud Dataflow, and Cloud Composer.
• Develop, maintain, and enhance data models in line with business requirements, optimising for performance and scalability.
• Collaborate with cross-functional teams to understand business needs, translate them into technical solutions, and provide data access solutions tailored to specific use cases.
• Conduct regular performance tuning, capacity management, and data quality checks to ensure the efficiency, security, and reliability of data infrastructure.
• Implement security best practices, including data encryption, access control, and compliance with organisational and regulatory standards.
• Develop and maintain comprehensive documentation on data architecture, data models, and processes.

Qualifications:

• Bachelor’s Degree in Computer Science, Information Systems, Engineering, or a related field.
• 3+ years of experience as a Data Engineer with hands-on expertise in designing, building, and optimising data architectures on GCP.
• Proficiency in SQL and Python for data transformation, automation, and integration.
• Strong knowledge of GCP tools: BigQuery, Cloud Dataflow, Cloud Storage, Cloud Composer (Apache Airflow), Pub/Sub, and Cloud Functions.
• Experience with data modelling, ETL processes, and data warehousing concepts.
• Experience with Apache Kafka or other streaming platforms is beneficial.
• Familiarity with CI/CD tools and DevOps practices for data pipelines, such as Docker, Terraform, or Kubernetes, is advantageous.

Skills:

• Analytical and problem-solving skills: Ability to diagnose complex data issues, recommend and implement solutions efficiently.
• Attention to detail and commitment to data quality: Ensures that data is accurate, reliable, and adheres to company standards.
• Communication and collaboration skills: Strong written and verbal communication abilities, capable of working well with both technical and non-technical stakeholders.
• Self-motivated and adaptable: Able to work independently in a fast-paced environment, with a proactive approach to learning and adopting new technologies.

Preferred Competencies:

• Certifications in Google Cloud (e.g., Professional Data Engineer) are a plus.
• Experience with machine learning workflows and integration with data pipelines.
• Knowledge of data governance principles and experience implementing data quality frameworks.