Gcp Data Engineer

Description – Data Engineer_GCP

Key Responsibilities

• Design, build, and optimise batch and streaming data pipelines using approved frameworks and tooling.
• Ensure pipelines are resilient, performant, and cost optimised.
• Implement monitoring, alerting, and automated recovery processes.
• Apply data quality checks and reconciliation processes to ensure accuracy and completeness.
• Maintain metadata, lineage, and documentation to support governance requirements.
• Adhere to role-based access control, data privacy, and security standards.
• Contribute to the development and maintenance of ingestion frameworks, transformation layers, and data models.
• Implement and maintain CI/CD pipelines for automated testing and deployment.
• Optimise data storage and retrieval strategies to meet performance needs.
• Work closely with Technical Leads, Data Architects, Analysts, and business stakeholders to deliver fit-for-purpose solutions.
• Participate in code reviews and knowledge-sharing sessions to improve team capability.
• Explore and adopt new tools, frameworks, and techniques to enhance engineering capability.
• Identify opportunities to automate and streamline workflows.

Key Skills & Experience

• Proficient in SQL for data wrangling, transformation, and analysis
• Strong programming skills
• Experience building ETL/ELT pipelines in cloud or distributed environments
• Familiarity with cloud platforms and services
• Knowledge of data modeling concepts
• Experience with data orchestration tools
• Familiar with version control and CI/CD pipelines
• Understanding of data quality, validation, and observability practices
• Works independently with minimal supervision on well-scoped tasks
• Collaborates effectively with stakeholders
• Communicates clearly and documents work for others to maintain or build upon
• Open to code reviews, feedback, and continuous learning
• Able to troubleshoot and resolve data pipeline failures or performance issues
• 2–4 years in a data engineering or closely related role
• Has delivered production-ready pipelines end-to-end
• Demonstrated ability to improve code quality, reliability, or performance

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