Architect and operate data-centric systems handling large-scale datasets on AWS
Focus on Snowflake optimization including data modeling, performance tuning, and cost efficiency
Design and orchestrate complex workflows using Apache Airflow
Build data transformations with dbt including modeling, testing, and documentation
Implement both real-time and batch data pipelines leveraging AWS services like S3
Manage core cloud infrastructure through Infrastructure as Code using Terraform
Ensure engineering excellence through CI/CD pipelines with GitHub Actions
Conduct comprehensive automated testing (unit, linting, integration, end-to-end)
Utilize observability tools like New Relic
Collaborate through Git/GitHub workflows

Strong Python development skills with ability to guide and mentor other engineers
Advanced SQL expertise with experience working with large-scale datasets
Deep experience with Snowflake including data modeling, optimization, and performance tuning
Solid understanding of architectural principles, microservices design, and data-centric systems
Hands-on with Apache Airflow for designing, orchestrating, and monitoring workflows
Experience with dbt for data modeling, transformations, and testing
Proven experience building and operating both real-time and batch data pipelines
Hands-on experience with AWS S3 and core cloud services
Strong experience with GitHub Actions or similar CI/CD technologies
Proficient with Git/GitHub and collaborative development workflows
Experience using Terraform for infrastructure management
Strong practices across unit testing, linting, integration, and end-to-end tests
Experience with structured, semi-structured, and unstructured data
Experience with monitoring platforms like New Relic or similar technologies
Fluent English (mandatory)

Senior Data Engineer, Python, Snowflake, Airflow, AWS

Key skills