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