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