Senior GCP Data Engineer

Project description

We are looking for the best people to help create the next big thing in digital banking.

Reason to join us

• We offer the opportunity to work in a highly professional environment where you will work with high-level financial instruments
• We want you to be part of our success story and give you reasons to be proud of what you achieved as part of our fabulous team
• We give you the opportunity to develop yourself and evolve in your career via our fantastic technical, business-related or soft skills training
• We encourage creative-thinking in our great open-minded work environment. Frequently the relaxation rooms are the place where the most ambitions ideas are born.
• We are not just professional teams, we are also friends who have fun working together
• The team is made up of enthusiastic professionals who work in an international environment, learning new technologies as part of client`s businesses.

Responsibilities

• Data Engineering & Architecture
• Design, develop, and maintain scalable data platforms and pipelines using Google Cloud services.
• Implement data ingestion, transformation, and orchestration workflows using:

  o BigQuery

  o Dataflow

  o Dataproc

  o Pub/Sub

  o Cloud Storage

  o Cloud SQL / PostgreSQL

• Define data models, partitioning strategies, and storage architectures optimized for large-scale analytics.
• Implement batch and near real-time data processing solutions.

  BigQuery Engineering

• Design, optimize, and maintain BigQuery datasets, tables, views, and data marts.
• Develop complex BigQuery SQL solutions for analytics and operational reporting.
• Optimize query performance, storage costs, partitioning, clustering, and workload management.
• Establish best practices for BigQuery governance, security, and performance monitoring.

  PostgreSQL Engineering

• Design and develop PostgreSQL database solutions on GCP.
• Create and optimize database schemas, indexes, stored procedures, and PL/pgSQL code.
• Perform database performance tuning, capacity planning, and troubleshooting.
• Support migration and modernization of legacy databases to PostgreSQL.

  Cloud Migration & Modernization

• Support migration of legacy Oracle workloads to PostgreSQL and BigQuery.
• Assess existing database architectures and recommend modernization approaches.
• Collaborate with application teams to refactor data solutions for cloud-native environments.
• Ensure data integrity, security, and operational readiness during migrations.

  Data Governance & Security

• Implement IAM controls, encryption, auditing, and data protection standards.
• Apply data governance and compliance requirements across the cloud platform.

  Collaboration

• Participate in architecture reviews, code reviews, and engineering standards definition.
• Collaborate with product owners, architects, analysts, and platform teams to deliver business value.

SKILLS

Must have

• Minimum 5 years of hands-on experience working with relational and analytical databases
• Minimum 1 year of hands-on experience with Google BigQuery (GCP)
• Proven expertise in Google BigQuery (GCP), with the ability to build, manage, and optimize data solutions in a cloud environment.
• Proven expertise in PostgreSQL administration and development, including schema design, data integrity, performance monitoring, and troubleshooting.
• Proficiency with GitHub for version control and collaborative development.

Nice to have

• Experience migrating Oracle databases to PostgreSQL and/or BigQuery.
• Oracle SQL and PL/SQL knowledge.
• Experience with Ora2pg or similar migration tooling.
• Google Cloud Professional Data Engineer certification.
• Google Cloud Professional Cloud Architect certification.
• Experience with Terraform.
• Experience with containerized deployments using Docker and Kubernetes (GKE).
• Experience with Airflow / Cloud Composer.
• Experience with data governance, metadata management, and data quality frameworks.
• Experience with Google Cloud Dataflow for building and managing data processing pipelines.
• Experience with Google Cloud Dataproc for big data processing and analytics workloads.
• Experience with Google Cloud Pub/Sub for event-driven architectures and real-time data streaming.
• Python for data engineering, automation, data processing, and scripting tasks.