Key skills
AirflowKubernetesSQLTerraformAIData EngineeringAnalyticsSnowflakedbtJiraConfluenceMentoring
About this role
Role Overview
- 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.