Our team is seeking an experienced Google Cloud Platform (GCP) Data Engineer with a strong background in building and optimising data pipelines, architectures, and data sets on GCP. This role involves close collaboration with data analysts, data scientists, and other stakeholders to ensure high-quality data availability for advanced analytics, machine learning, and real-time data processing.

Key Responsibilities:

• Design, build, and maintain scalable ETL/ELT data pipelines on GCP to support analytics, reporting, and machine learning applications.

• Implement and manage data warehouses and data lakes using GCP services such as BigQuery, Cloud Storage, Cloud Dataflow, and Cloud Composer (Airflow).

• Develop and optimise data models to align with business needs, ensuring scalability and performance.

• Collaborate with cross-functional teams to understand business requirements and deliver tailored data access solutions.

• Ensure data quality, security, and governance through performance tuning, capacity management, and compliance best practices.

• Implement CI/CD automation using GitHub Actions and Docker to streamline deployment of data pipelines.

• Develop and maintain documentation for data architecture, models, and processes.

• Support real-time data processing with tools such as Kafka Streaming and MLOps workflows for machine learning pipelines.

Qualifications:

• Bachelor’s Degree in Computer Science, Information Systems, Engineering, or a related field.

• 4+ years of experience in data engineering, with at least 2 years focused on GCP.

• Strong experience with SQL and ETL/ELT processes for transforming and processing large-scale structured and unstructured data.

• Solid understanding of data warehousing concepts and dimensional modelling techniques.

• Hands-on experience with BigQuery or Snowflake, as well as orchestration tools like Airflow or Argo.

• Experience working with real-time data processing using Kafka Streaming.

• Knowledge of machine learning pipelines and MLOps practices is a plus.

Technical Skills:

• Google Cloud Platform (GCP) – BigQuery, Cloud Dataflow, Cloud Storage, Cloud Composer.

• SQL & DBT – Data modelling and transformation within Medallion Architecture.

• Python – Development of data workflows, automation, and integration.

• Kafka Streaming – Real-time data processing.

• GitHub & CI/CD (GitHub Actions) – Version control and automated deployment.

• Docker & Kubernetes (GKE) – Containerisation and orchestration.

• Airflow (Cloud Composer) – Data pipeline orchestration.

Preferred Competencies:

• Google Cloud Certification (e.g., Professional Data Engineer) is a plus.

• Experience with data governance and data quality frameworks.

• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.

• Familiarity with machine learning workflows and MLOps integration.

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