Data Engineer

Data Engineer (Python & GCP) 
Minimum Experience: 10+ Years
Location: Phoenix, Arizona (Hybrid) 
Position: Contract​

Note: Please don’t share AWS Data Engineer Candidates.

Key responsibilities
Design and build scalable ETL/ELT data pipelines for batch and real-time use cases using Python, Dataflow, Dataproc, Pub/Sub, Kafka, and related services.​
Implement and optimize data warehousing and analytics solutions on BigQuery and Cloud Storage, following best practices in performance, cost, and reliability.​
Architect, document, and troubleshoot cloud-native data platforms, ensuring high availability, monitoring, and CI/CD-based deployments.​
Collaborate with business stakeholders to analyze requirements, translate them into technical designs, and deliver robust, production-grade data solutions.​

Required experience
10+ years total IT experience with 6+ years in Data Engineering focused on data warehousing and analytics.​
4+ years strong Python (including notebooks) and 4+ years building scalable data pipelines (extraction, transformation, loading).​
4+ years on a major public cloud and 2+ years hands-on GCP (Dataflow, Dataproc, Cloud Composer/Airflow, BigQuery, Cloud Storage, GKE, Pub/Sub).​
2+ years with Kafka, Pub/Sub, Docker, Kubernetes, and experience in architecture design and documentation.​
Strong understanding of relational and dimensional data modeling, plus DevOps/CI/CD experience.​

Soft skills
Ability to work independently in a hybrid setup, proactively solve problems, and keep stakeholders updated.​
Excellent written and verbal communication skills, including technical documentation and interaction with senior business leaders