PBT Group, with in-depth knowledge of Business Intelligence solutions and experience that spans more than two decades in over 25 countries, PBT Group has engaged with many of the Top 100 companies, answering to diverse needs to give clients not only a competitive edge, but also a sustainable advantage. Worldwide expertise and local wisdom - that’s what mak...
Read more about this company
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.
20 Initiatives to Boost Employee EngagementAre you struggling with improving employee engagement at work? This article covers everything from better communication to building a strong workplace culture.
30 Common Interview Mistakes to AvoidThis piece examines 30 of the most common mistakes applicants make at interviews, so you know how to better avoid them.
Gmail
Yahoomail