Cloud Zero's Data Engineering Leader
4 days ago
About CloudZero
Cloud cost management is one of the biggest challenges organizations face today. With cloud adoption accelerating, complexities and costs are on the rise – and macroeconomic conditions only increase pressure to prove cloud efficiency. To tackle this issue, CloudZero was founded in 2016 with a mission to make efficient innovation a reality for every cloud-driven organization.
The Problem We're Solving
In today's fast-paced business environment, engineering decisions often bypass the cost conversation. At CloudZero, we believe that every engineer drives buying decisions, yet they're frequently left out of the cost discussion. Our goal is to change this by providing a dynamic, single-page application that answers complex data-heavy questions every cloud-based organization needs to ask to grow profitably.
Our Solution
We've built a cutting-edge SaaS platform at the intersection of next-generation cloud cost management and FinOps. By ingesting billing and usage data from all cloud, SaaS, and PaaS providers, organizing it in real-time according to customers' business structures, and empowering them to make informed business decisions, our platform is revolutionizing the way companies approach cloud cost management.
Your Role as Data Engineering Leader
As a seasoned leader in Data Engineering, you will play a pivotal part in building and scaling our data infrastructure. Your expertise in Snowflake architecture, performance tuning, and cost optimization will be instrumental in developing scalable, reliable, and secure data pipelines and architectures using modern technologies. You will lead the design and implementation of innovative data solutions, collaborate with analytics and business intelligence teams, and define and enforce data governance policies.
What We're Looking For
We're seeking an experienced leader with 8+ years of experience in data engineering, including at least 3 years in a lead or principal role. You should have strong proficiency in SQL and data modeling best practices, as well as hands-on experience with ETL/ELT tools like dbt, Matillion, or Airflow. Familiarity with cloud platforms like AWS, Azure, or GCP is also essential. A proven track record of designing and implementing scalable data pipelines in large-scale environments, strong communication skills, and the ability to work effectively with both technical and non-technical stakeholders are must-haves. Experience with real-time data processing technologies, knowledge of machine learning pipelines, and certifications in Snowflake, Looker, or cloud platforms are highly desirable.
Estimated Salary: $180,000 - $250,000 per year
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