We are looking for a Senior Data Engineer with strong experience in modern cloud data platforms and data pipeline development. In this role, you will design, build, and maintain scalable data pipelines and transformation workflows using a modern data stack centered around Snowflake, dbt, and Apache Airflow.
The position combines data engineering expertise with DataOps practices, focusing on automation, reliability, and scalability of data workflows. You will work closely with analytics, product, and engineering teams to ensure the delivery of high-quality datasets and data products.
Design, develop, and maintain data pipelines and ELT workflows within a modern cloud data platform
Build and manage data transformation models using dbt, including testing, documentation, and modular modeling
Orchestrate and monitor data workflows using Apache Airflow
Manage and optimize Snowflake data warehouse environments, focusing on performance and cost efficiency
Implement DataOps practices, including CI/CD pipelines, automated testing, and deployment for data workflows
Ensure data quality, reliability, and observability across the data platform
Collaborate with analytics, product, and engineering teams to deliver reliable datasets and data products
Improve monitoring, automation, and operational processes for the data platform
7+ years of experience in Data Engineering or similar roles
Strong hands-on experience with:
Snowflake
Apache Airflow
dbt (data build tool)
Advanced SQL skills
Experience designing and managing ELT pipelines
Experience using Git and collaborative development workflows
Familiarity with DataOps practices and CI/CD pipelines for data workflows
Solid understanding of data modeling and data warehouse architecture
Experience with cloud platforms such as AWS, Azure, or GCP
Familiarity with containerization technologies such as Docker
Experience with Infrastructure as Code tools (e.g., Terraform)
Experience with data quality, monitoring, or observability tools
Exposure to data governance frameworks
Senior engineer capable of owning components of a data platform
Comfortable working at the intersection of data engineering and operational platform management
Strong focus on automation, reliability, and scalable data workflows
Experience collaborating with cross-functional teams, including analytics, product, and engineering stakeholders