Senior BigQuery Engineer facilitating data quality and migrating to cloud-native ecosystems at Deutsche Bank. Working with large-scale financial datasets in an agile environment.
Responsibilities
Design, develop, and maintain scalable data warehouse solutions in BigQuery, including dataset architecture, schema design, and data modeling (star/snowflake)
Design and implement a cloud-native data warehouse to replace on-premises infrastructure
Optimize performance through partitioning, clustering, query tuning, and workload management
Build data processing pipelines and workflows feeding BigQuery from multiple sources
Implement data quality checks, validation frameworks, and reconciliation processes
Work closely with product owners, analysts, to ensure solution align with the business requirements specification
Requirements
University degree in computer science or a comparable qualification
At least 5 years of data engineering experience
Strong SQL knowledge, preferably on Google Cloud Platform (GCP)
Experience orchestrating workflows with Cloud Composer (Apache Airflow), including DAG development, scheduling, monitoring, and dependency management
Hands-on experience building data processing pipelines using Dataflow (batch and streaming)
Good understanding of data warehousing concepts, data flows, data feeds
Experience using Bitbucket for Git-based source control and collaboration
Ability to work collaboratively in a dynamic environment
Bonus Skills: Hands-on experience with Python/PySpark for scalable distributed data processing
Experience with Infrastructure as Code (Terraform, Ansible, Chef)
Knowledge of shell scripting
Experience in financial services or regulated environments
Benefits
New beginnings can be a challenge. We promise a smooth integration and a supportive mentor
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