Data Scientist CloudOps
New York City, New York
Expiry Date :
Fri, 06 Nov 2020 23:59:59 GMT
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We’re on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scaletrillions of data points per dayproviding always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way.
The Cloud Cost Optimization team works directly with the CTO and is responsible for identifying and executing on cost-saving opportunities, providing engineering teams actionable visibility into spend, and empowering finance to understand and incorporate the complexities of cloud costs.
As a Data Scientist on the CloudOps team, youll work with and analyze usage and billing data generated from cloud applications. Datadog operates in sophisticated multi-cloud, multi-region, classical, containerized, and serverless environments, and you will be responsible to unify these disparate sources and disentangle their primary cost drivers. You will share your work directly with the highest levels of leadership at Datadog and it will have an impact on the direction of the engineering organization.
Build marginal cost models using cloud usage and cost data, and use these models to discover trends and build forecasts
Own and refine cloud provider billing data ingestion pipelines
Develop new ways to understand the relationship between cloud resource consumption in complex containerized environments and business drivers
Think deeply about what data and actionable views to surface from CxO down to individual engineers deploying new projects
Develop metrics that bring clarity too complicated environments including containers, shared resources, and bespoke cost variables.
Youve worked with leadership to define a problem space, select questions to be answered, and created repeatable compelling reporting to solve stakeholder understanding
You have experience creating and maintaining data ETL pipelines using Spark, Luigi, Airflow, and other open-source technologies using programming languages like Python, Scala, SQL
Youre comfortable spending the day in notebooks (Zeppelin, Jupyter, Observable, etc) and have frequently used notebooks to share findings and create insight for yourself and others
You enjoy getting to the bottom of arcane data sets; and creating logic to make those same datasets understandable to the masses
Youre comfortable with ambiguity in the early stages of a project; and appreciate the work needed to determine the how in reaching an objective
Youre familiar with cloud infrastructure; and what an engineers may consider when deciding on a serverless solution, or a particular cloud server.
You have a BS/MS/PhD in a scientific/quantitative field or equivalent experience
Have previously worked with cloud provider billing data
Interested in business outcomes, high impact projects that have a tangible result on business metrics. Youve worked on these projects in the past and are eager for more.
Youve faced a tradeoff between increasing infrastructure cost or increasing the cost to team time. Youve been woken up by infrastructure alarms.
You hold some strong opinions on the features in AWS Cost Explorer, the GCP billing console, or Azure Cost Management + Billing