Data Cloud Engineer (GCP)

Role Overview

We are seeking a Data Cloud Engineer to design, build, and operate scalable data platforms on Google Cloud Platform (GCP) that power advanced AI-driven analytics, credit-risk modeling, and fintech products.

In this role, you will develop cloud-native data pipelines and modern data architectures that enable Data Science, Business Intelligence, and AI initiatives across the organization. You will work closely with data scientists, analysts, and business stakeholders to ensure that reliable, well-governed, and analytics-ready data is available to support credit risk models, data-driven decision-making, and product innovation. A strong focus of this role is ensuring high standards of data quality, data consistency, and data governance across the entire data platform.

This position offers the opportunity to work with large-scale financial datasets, modern cloud technologies, and advanced analytics in a fast-growing fintech environment, contributing directly to the development of data products and intelligent financial solutions. You will also have the opportunity to work closely with and be mentored by a senior leader with extensive international experience in Artificial Intelligence, Data Science, and credit risk modeling.

Key Responsibilities

Cloud Data Architecture

• Design, build, and maintain scalable cloud-native data pipelines on Google Cloud Platform.
• Develop robust data ingestion, transformation, and orchestration workflows supporting analytics, BI, and machine learning applications.
• Ensure high levels of performance, reliability, and scalability across the data platform.

Data Platform & Analytics Enablement

• Build and maintain analytics-ready datasets used for Power BI dashboards and enterprise reporting.
• Design and maintain data models and semantic layers optimized for analytics and business insights.
• Enable Data Science and AI teams with high-quality datasets and efficient data pipelines.

Data Integration & Governance

• Integrate multiple internal and external data sources into the cloud data platform.
• Implement data quality frameworks, monitoring, and validation processes to ensure trusted data assets.
• Apply GCP security best practices, including access control, data protection, and compliance policies.

Optimization & Performance

• Optimize data workflows for performance, scalability, and cost efficiency within the GCP ecosystem.
• Improve pipeline performance, query optimization, and resource utilization.

Collaboration & Technical Leadership

• Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.
• Provide guidance on data engineering best practices and cloud architecture.
• Contribute to continuous improvement of the organizations data platform and data strategy.