Design and build a scalable, high-performance data layer used across internal teams and external client-facing use cases
Optimize and refactor existing data models in Snowflake to improve efficiency, maintainability, and performance
Develop and maintain reliable, production-grade data pipelines that ensure accuracy, timeliness, and consistency of business-critical data
Implement infrastructure and orchestration improvements that strengthen platform stability, scalability, and observability
Collaborate with analytics and product teams to define data requirements and translate them into scalable data solutions
Conduct code reviews and mentor team members to elevate engineering standards and promote best practices
Participate in on-call rotations and incident response processes to maintain 24/7 data platform reliability
Contribute to architectural decisions and long-term roadmap planning to ensure the data platform supports future business growth
Requirements
5 to 10 years of relevant experience in data engineering
Advanced proficiency in Snowflake and SQL, demonstrated by designing performant queries, optimizing warehouse usage, and improving cost efficiency across large-scale datasets
Strong experience with dbt and dimensional data modeling, including building modular, scalable models and enforcing testing and documentation standards
Proven experience building and orchestrating data pipelines using tools such as Airflow, Meltano, or similar orchestration frameworks in production environments
Experience working with infrastructure-as-code and containerized environments, such as Kubernetes and Terraform, supporting reliable and reproducible data platform deployments
Demonstrated ability to design data architectures that scale with increasing data volume and concurrency, reducing bottlenecks and improving system reliability
Experience leading or contributing to complex data engineering projects, managing tasks through tools such as Jira and Confluence, and delivering against defined milestones
Proven experience mentoring data engineers, conducting code reviews, and elevating team standards through shared best practices
Experience operating in environments with production support responsibilities, including on-call rotations and incident resolution processes
Ability to collaborate cross-functionally with analytics, product, engineering, and business stakeholders to translate data requirements into robust technical solutions
Ability to leverage AI tools and technologies relevant to data engineering workflows, such as AI-assisted query optimization, pipeline monitoring, documentation generation, or anomaly detection
Tech Stack
Airflow
Kubernetes
SQL
Terraform
Benefits
We take care of our people with a comprehensive benefits package designed to support your well-being, growth, and success.