About the Role
We are seeking an experienced Data Engineer to join a leading financial services organization undergoing significant cloud and data transformation. This role will be responsible for designing, building, and maintaining scalable data platforms and pipelines on Google Cloud Platform (GCP) to support enterprise reporting, regulatory compliance, risk management, customer analytics, and strategic decision-making.
Working closely with business stakeholders, architects, data analysts, and engineering teams, you will deliver secure, high-quality, and reliable data solutions within a complex and highly regulated environment.
Key Responsibilities
- Design, develop, and maintain scalable batch and real-time data pipelines using GCP technologies.
- Build enterprise-grade data solutions leveraging Big Query, Dataflow, Cloud Composer, Pub/Sub, Cloud Storage, and Dataproc.
- Develop data ingestion frameworks to integrate data from core banking, finance, risk, customer, and operational systems.
- Design and maintain data warehouses, data lakes, and analytical data models to support business and regulatory reporting requirements.
- Ensure data quality, lineage, governance, security, and compliance with financial industry standards and regulatory obligations.
- Implement Infrastructure as Code (IaC) using Terraform and support automated deployment through CI/CD pipelines.
- Collaborate with technology and business teams to deliver data solutions that support risk, finance, compliance, treasury, and customer analytics functions.
- Optimize data processing performance, storage efficiency, and query execution across large-scale datasets.
- Support audit, regulatory, and governance initiatives through accurate and reliable data management practices.
- Monitor, troubleshoot, and resolve data platform and pipeline issues to ensure operational stability.
Required Skills & Experience
- 7+ years of experience in Data Engineering, Data Warehousing, or related disciplines.
- Strong hands-on experience with Google Cloud Platform (GCP).
- Proven expertise in Big Query, Cloud Composer (Apache Airflow), Pub/Sub, Cloud Run
- Strong programming experience in Python SQL
- Experience building enterprise ETL/ELT solutions and data integration frameworks.
- Strong understanding of data modelling techniques, including dimensional modelling.
- Experience with Terraform and Infrastructure as Code methodologies.
- Knowledge of CI/CD, Git, DevOps, and cloud-native engineering practices.
- Experience working with large-scale structured and semi-structured datasets.
- Experience within banking, wealth management, financial services, insurance, or other highly regulated industries is highly regarded.
- Exposure to risk, finance, regulatory reporting, compliance, anti-money laundering (AML), or customer data domains is advantageous.
- Understanding of data governance, privacy, security, and regulatory compliance requirements.
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