Senior Data Engineer, Cloud Platform Modernization
Overview
You own the design and build of scalable data pipelines and cloud-based platforms for a major enterprise. 5+ years of experience with Python, SQL, and AWS underpins your work. You partner with cross-functional teams to modernize legacy data systems, driving real-time analytics and data-driven decisions. This long-term contract in Glendale, CA offers a hybrid schedule and W2 pay.
What You'll Do8
- 1Design and implement modern data architectures on AWS, including S3, Redshift, and Kinesis.
- 2Build and optimize ETL pipelines using Spark and Airflow to process terabytes of data.
- 3Lead migration of on-premise data warehouses to cloud-native solutions.
- 4Collaborate with data scientists and analysts to deliver reliable, high-quality data.
- 5Develop and maintain data models for business intelligence and reporting.
- 6Implement data governance and security best practices across the platform.
- 7Monitor and troubleshoot data pipelines to ensure performance and reliability.
- 8Mentor junior engineers on coding standards and cloud technologies.
Requirements9
- 15+ years in data engineering, building scalable data pipelines.
- 2Proficiency in Python and SQL for data processing and transformation.
- 3Hands-on experience with AWS services (e.g., EC2, S3, Redshift, Glue).
- 4Experience with Apache Spark and Airflow for orchestration.
- 5Strong knowledge of data modeling, warehousing, and ETL principles.
- 6Bachelor's degree in Computer Science or equivalent experience.
- 7Experience with Kafka or Kinesis for streaming data.
- 8Familiarity with Docker and Kubernetes for containerized deployments.
- 9Excellent communication and cross-functional collaboration skills.
Salary Insight
$78 - $83k per year
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