The Challenge
Apptio Cloudability is the expert in cloud spend management and optimization. We work with some of the biggest cloud spenders to optimize the cost and efficiency of their cloud infrastructure. Our platform monitors a significant part of public cloud spend and helps save our customers millions of dollars. Building our application requires a deep understanding of our problem domain and a passion for technical challenges. As a Staff Software Development Engineer, you will work closely with your team to build and iterate on critical parts of the Cloudability application while honing your craft.
The Role
As a Staff Software Development Engineer at Apptio Cloudability, you will work closely with the Engineering team, Data Scientists, Product Managers and Designers to iteratively deliver new Cost Optimization features, to help our customers discover new savings opportunities. You will help design and engineer effective software solutions that run at ‘cloud-scale’. You will participate in design, architecture and code reviews, foster collaboration, and guide the team through roadmap deliverables and other technical challenges. Above all, you will work as a leader of the team to provide our customers with a great product while helping to grow a strong engineering team.
REQUIREMENTS
- Possess a burning desire to design and implement scalable, pragmatic solutions to complex problems
- Proficient with Java, Go or a C-based language
- Experience with Postgres, MySQL or other relational database technologies
- Desire to operate and excel in a dev-ops team
- Competent with Git and CI/CD pipelines
- Comfortable with fast moving software design and development methodologies
- Capable of contributing to technical conversation and decisions with well thought out opinions
Bonus Stuff:
- Experience with Service Oriented Architectures, modern API designs and implementations
- Familiarity with Machine Learning and/or related technologies (Apache Spark, DataFrames, Pandas etc.)
- Expertise with popular AWS, Azure and/or GCP services for compute, storage and databases etc.
- Familiar navigating the nuances of 3rd party integrations with applications, APIs and SaaS/PaaS providers
In a Typical Week You Will
- Understand the on-going work in the team and along with the engineering team, data scientists, product managers and plan for the upcoming tasks within the sprint and beyond.
- Understand the problem space, the competitive landscape and constraints and help deliver engineering solutions that work both for the customer and Apptio
- Commit code to our production systems as well as participate in the testing and validation of new Cost Optimization features
- Participate in design/code reviews, collaborate, and provide direction
- Join daily standups to discuss project status, new projects, and blocking issues.
- Help lead communities of practice, technical lunch & learn sessions, and engineering book clubs to continue learning
The Interview Process
- You apply for an open position.
- If your application is a good match for the role, you will have a chat with the recruiter to understand the position and the team. Afterwards, you will be asked to participate in an aptitude test and later, a technical phone-screen with a member of the team.
- If all goes well, we will have you come into our office for an in-person interview. You will meet with members of several teams: engineering, product and/or design.
- We commit to making a decision and following up with an offer or an explanation within a week. We are happy to work through the process on a timeline that respects your schedule and current employment status.
The Team
The Cost Optimization team is a cross-functional engineering team in charge of building and maintaining the services and UI that serve cost saving opportunities. We analyze utilization patterns using Machine Learning to generate actionable recommendations that help our customers use the Cloud more efficiently. The Cost Optimization team spans two sites, located in Bellevue, WA and Portland, OR. The team operates on a dev-ops model and participates in a shared on-call rotation.
