Data Engineer

We are seeking a highly skilled Data Engineer (Contractor) to support the development and optimisation of data pipelines within our Google Cloud Platform (GCP) environment. The ideal candidate will have strong experience building Spark pipelines (Scala preferred), working with BigQuery, and writing efficient Unix scripts to support large-scale data processing. You will collaborate with data engineering teams to design, build, and maintain high-performance data pipelines that enable analytics, reporting, and business insights.

Responsibilities:

• Design, develop, and deploy data ingestion and transformation pipelines using Apache Spark (Scala).
• Work within Google Cloud Platform (GCP) components including Dataproc, BigQuery & Cloud Storage.
• Write complex SQL queries for data analysis, validation, and transformation in BigQuery.
• Develop Unix shell scripts for automation, data movement, and pipeline orchestration.
• Optimise and troubleshoot data pipelines for performance, scalability, and reliability.
• Collaborate with data engineers, analysts, and business stakeholders to understand requirements and ensure data quality.
• Contribute to code reviews, documentation, and CI/CD integration of data workflows.

Requirements:

• 4-6 years of hands-on experience in data engineering or related roles.
• Proven experience developing Spark applications in Scala.
• Strong experience working in the Google Cloud Platform (GCP) ecosystem, including Dataproc, BigQuery, and Cloud Storage.
• Proficient in SQL (especially BigQuery SQL dialects).
• Strong experience with Unix/Linux scripting for data automation.
• Familiarity with version control (Git) and CI/CD processes.
• Excellent problem-solving and debugging skills.
• Strong communication and documentation abilities.
• Experience with Python for data processing or automation.
• Knowledge of data governance, data quality, or metadata management best practices.
• Bachelor's degree in Computer Science, Engineering, or a related technical discipline (or equivalent work experience).