Data Engineer (Multi-Cloud & Data Integration)

Job Summary

We are seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and integrations across multi-cloud environments. The ideal candidate will be responsible for ensuring reliable, efficient, and cost-effective data delivery to support analytics, reporting, and business operations. This role requires strong expertise in Python, SQL, data warehousing concepts, ETL/ELT development, and cloud-based data platforms.

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data across hybrid cloud environments, including AWS, Google Cloud Platform (GCP), and Oracle Cloud.
• Build scalable and reliable data integration solutions that support analytics, reporting, and operational use cases.
• Implement and maintain data quality frameworks, including validation, reconciliation, monitoring, and error-handling processes.
• Optimize pipeline performance, storage utilization, compute resources, and query efficiency, with particular emphasis on Google BigQuery cost and performance optimization.
• Create, maintain, and enhance workflow orchestration processes using Apache Airflow.
• Develop and maintain comprehensive technical documentation for data pipelines, workflows, and integration processes.
• Collaborate with cross-functional teams, including data analysts, architects, and business stakeholders, to understand data requirements and deliver effective solutions.
• Support deployment automation and code management using modern Git, CI/CD, and DevOps practices.
• Monitor and troubleshoot data workflows to ensure high availability, reliability, and data integrity.

Required Skills & Qualifications

• Strong proficiency in Python and SQL.
• Hands-on experience designing and maintaining ETL/ELT pipelines.
• Experience working with cloud environments such as AWS, GCP, and/or Oracle Cloud Infrastructure (OCI).
• Solid understanding of data warehousing concepts, including:
  • Star Schema Design
  • Dimensional Modeling
  • OLTP vs. OLAP Architectures
• Experience with Google BigQuery optimization and performance tuning.
• Knowledge of data quality management, validation rules, and reconciliation processes.
• Experience with Apache Airflow for workflow orchestration and scheduling.
• Proficiency with Git, version control systems, and CI/CD pipelines.
• Understanding of modern DevOps methodologies and automation practices.

Preferred Qualifications

• Experience working in multi-cloud or hybrid cloud environments.
• Knowledge of data governance, data security, and compliance best practices.
• Familiarity with infrastructure-as-code and cloud-native data services.
• Experience supporting analytics, business intelligence, and reporting platforms.

Education & Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant experience in Data Engineering, Data Integration, or Cloud Data Platforms.