DataOps/ Analytics Engineer

We're looking for highly talented, experienced, passionate, and data-driven DataOps/ Analytics Engineer.
This role bridges the gap between data engineering and analytics teams, focusing on the orchestration, maintenance, and optimization of our analytics infrastructure.
Orchestration Pipelines: Design and manage data orchestration pipelines using Dagster.
Data Modeling: Develop and enforce guidelines and standards for data modeling in dbt, ensuring comprehensive documentation and adherence to best practices.
Data Warehousing: Maintain and optimize our BigQuery data warehouse, focusing on performance monitoring, cost management, and data quality.
Data Catalog Management: Enhance and maintain our Data Hub data catalog.
CI/CD Management: Implement CI/CD processes, orchestration pipelines, and automated data quality monitoring to streamline workflows and reduce manual interventions.
Infrastructure Management: Utilize Kubernetes for hosting, and manage associated tools such as Elasticsearch and Grafana.
Data Quality: Implement and monitor data quality processes, including alerting and reporting mechanisms.
Development Workflow Optimization: Improve and maintain development workflows to ensure efficient and seamless data product delivery.
Collaborative Design: Work alongside business users and data analysts to design and build data models that enhance data discovery and analyses.
Standards and Best Practices: Contribute to internal standards for style, maintainability, and best practices for a high-scale data infrastructure.
Documentation and Scalability: Maintain documentation, manage technical debt, and ensure scalability of infrastructure.