Senior BigQuery Engineer

Role description

• You will design and deliver high-performance data solutions supporting complex reporting functions, as well as migrating on-premises platforms to modern cloud-based ecosystems;
• You will work with large-scale financial datasets, ensuring secure, compliant, and low-latency data solutions that enable analytics and decision-making across the organization;
• You will design, develop, and maintain scalable data warehouse solutions in BigQuery, including dataset architecture, schema design, and data modeling (star/snowflake);
• You will design and implement a cloud-native data warehouse to replace on-premises infrastructure;
• You will optimize performance through partitioning, clustering, query tuning, and workload management;
• You will build data processing pipelines and workflows feeding BigQuery from multiple sources;
• You will implement data quality checks, validation frameworks, and reconciliation processes;
• You will work closely with product owners, analysts, to ensure solution align with the business requirements specification.

Qualifications

• 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;
• 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