Data Engineer delivering high-performance data solutions for a leading technology and consulting company. Involves building scalable cloud platforms and enabling data-driven decisions.
Responsibilities
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.
Requirements
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.
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