Lead Data Engineer Specializing in AWS and DBT Frameworks

Elevate data engineering efforts as a Lead Data Engineer in a cloud-centric AWS setup. Specialize in streaming architectures and big data warehousing solutions to meet client needs. This role is all about implementing large-scale data engineering solutions while focusing on streaming data architecture and delivering high-performance outcomes. You will guide architectural decisions, define best practices for data modeling, and ensure seamless DBT implementation.

Experience in AWS services, particularly with Redshift and error-handling frameworks, is crucial for your success in this role. Key Responsibilities:

• Direct architecture for streaming data from GCP to AWS
• Create resilient data ingestion frameworks incorporating monitoring
• Employ Spark/PySpark for distributed processing pipelines
• Maintain scalable warehouses and ETL processes using DBT
• Lead performance tuning for Redshift and ensure best practices Requirements:
• Over 6 years of big data engineering experience
• Successful history in streaming architecture development
• Expertise in optimizing Amazon Redshift performance
• Familiarity with CI/CD pipeline creation for data
• Client-facing delivery experience is a must Apply your engineering skills to produce leading-edge streaming solutions that maximize data efficacy and integrity.