About the Role
We are seeking an experienced
Google Cloud Data Engineer
to join our growing cloud and data practice, supporting enterprise customers in designing, building, and optimizing modern data platforms on Google Cloud Platform (GCP).
As a trusted technical expert, you will work closely with customer stakeholders, architects, data scientists, analysts, and engineering teams to deliver scalable, secure, and high-performing data solutions. You will be responsible for developing data pipelines, enabling advanced analytics, supporting AI/ML initiatives, and ensuring enterprise-grade governance and security across cloud data ecosystems.
This is an excellent opportunity to work on large-scale digital transformation programmes, helping organisations unlock the value of their data through modern cloud technologies.
Mandatory Certification Requirement
Candidates must hold a current Google Cloud Professional Data Engineer certification.
Applications from candidates who do not possess this certification will not be considered.
Additional Google Cloud certifications are highly desirable.
What You'll Be DoingData Platform Engineering
Design and implement enterprise-scale data platforms on Google Cloud.
Build robust, scalable, and resilient batch and real-time data pipelines.
Develop data ingestion, transformation, and orchestration frameworks.
Support data lake, data warehouse, and lakehouse architectures.
Data Integration & Pipeline Development
Build and maintain data pipelines using:
Dataflow
Dataproc
Cloud Composer
Pub/Sub
BigQuery
Cloud Storage
Integrate data from on-premise, SaaS, and multi-cloud sources.
Optimise ETL/ELT processes for performance, reliability, and cost efficiency.
Analytics & AI Enablement
Enable advanced analytics and reporting capabilities using BigQuery.
Support AI and machine learning initiatives through high-quality data engineering practices.
Collaborate with data scientists and ML engineers to operationalise data products.
Prepare and manage datasets for Vertex AI and predictive analytics solutions.
Data Governance & Security
Implement enterprise data governance standards.
Ensure compliance with security, privacy, and regulatory requirements.
Design data access controls using IAM and policy management.
Implement data quality, lineage, and observability frameworks.
Performance & Optimisation
Monitor and optimise BigQuery workloads and cloud resource utilisation.
Drive FinOps best practices for cloud data platforms.
Improve performance, scalability, and reliability of enterprise data solutions.
Customer Engagement
Work directly with enterprise customers to gather requirements and define technical solutions.
Participate in workshops, architecture reviews, and design sessions.
Communicate technical concepts clearly to both technical and non-technical stakeholders.
Act as a trusted advisor on cloud data best practices.
Essential Skills & ExperienceCertifications (Mandatory)
Google Cloud Professional Data Engineer (Current and Active)
Highly Desirable Certifications
Professional Cloud Architect
Professional Cloud DevOps Engineer
Professional Cloud Security Engineer
Databricks Data Engineer Associate/Professional
Snowflake SnowPro Certification
Microsoft Fabric Certification
Experience
5+ years of experience in Data Engineering.
3+ years of hands-on Google Cloud Platform experience.
Proven experience delivering enterprise-scale data solutions.
Experience working with large, complex datasets in production environments.
Experience supporting business-critical data and analytics platforms.
Technical SkillsGoogle Cloud Services
Strong experience with:
BigQuery
Dataflow
Dataproc
Pub/Sub
Cloud Storage
Cloud Composer
BigLake
Dataplex
Vertex AI
Cloud Functions
Cloud Run
Data Engineering
ETL/ELT Development
Data Warehousing
Lakehouse Architectures
Data Modelling
Data Governance
Data Quality Management
Metadata Management
Programming & Development
SQL (Advanced)
Python
PySpark
Apache Beam
Git Version Control
DevOps & Automation
Terraform
CI/CD Pipelines
Infrastructure as Code
GitHub Actions / GitLab CI/CD
Cloud Build
Databases & Analytics
Experience with one or more:
BigQuery
PostgreSQL
SQL Server
Oracle
Snowflake
Databricks
MongoDB
Soft Skills
Excellent communication and stakeholder management skills.
Strong analytical and problem-solving capabilities.
Ability to translate business requirements into technical solutions.
Comfortable working directly with enterprise customers.
Strong collaboration and teamwork skills.
Self-motivated with a passion for learning and innovation.
Desirable Experience
Experience working in one or more of the following sectors:
Financial Services
Retail & eCommerce
Manufacturing
Healthcare
Telecommunications
Public Sector
Experience with:
Data Mesh architectures
Real-time analytics platforms
Master Data Management (MDM)
AI/ML operationalisation
Multi-cloud data strategies
What Success Looks Like
In this role, you will:
Deliver scalable and secure cloud data solutions for enterprise customers.
Improve data accessibility, reliability, and governance.
Enable advanced analytics and AI capabilities.
Drive measurable business value through modern data engineering practices.
Contribute to customer success and long-term cloud adoption strategies.