Lead Data Engineer designing streaming architectures and data warehouses at Two Circles. Collaborate with clients and integrate streaming data from GCP into AWS environments.
Responsibilities
Own the architectural direction for streaming data ingestion from GCP into AWS
Design resilient ingestion frameworks including error handling, retry strategies, monitoring, and failure isolation
Implement distributed processing pipelines using Spark / PySpark or similar frameworks
Create and maintain scalable data warehouses and associated ETL/ELT processes using DBT models in Amazon Redshift
Design and implement DBT projects including macros, tests, documentation, and reusable modeling patterns
Conduct Redshift query and DBT performance tuning to optimize warehouse efficiency and cost
Define and enforce best practices for:
Data modeling
Version control (Git-based workflows)
CI/CD pipelines for DBT deployments
Automated testing at model, transformation, and pipeline levels
Ensure robust testing is embedded into every DBT model (schema tests, custom tests, data validation checks)
Lead code reviews and architectural design reviews
Work with AWS services including Redshift, S3, Glue, Step Functions, Lambda (Python), Athena, and EMR
Requirements
6+ years of data engineering experience in big data environments
Proven experience designing and implementing streaming architectures
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