Description

CECM Principal Software Engineer (Big Data) Job Description

The Salesforce Cloud Economics and Capacity Management (CECM) team is looking for a Principal Engineer with experience across Big Data and Infrastructure to join us!

You will be working with a group of world-class engineers, architects, and product managers to build the breakthrough features that our internal customers will love, adopt and use while ensuring stable and scalable applications. You will also be working with data scientists to innovate and deliver analytics solutions using Big Data analytics technologies. You'll be a part of a modern, lean, self-governing product engineering team where you have the ability to switch hats between coding to requirements gathering, to testing for quality and performance.

CECM develops intelligent, data driven tools which enable strategic decision-making pertaining to Salesforce infrastructure expenditure and capacity management. We are building a platform that provides near real-time monitoring of cost and capacity utilization of the infrastructure, which will help in optimizing resource allocation and minimizing costs. We apply advanced machine learning techniques to turn the petabytes of data generated by our global infrastructure into actionable predictions and business insights used by capacity planners, internal service owners, and technical leaders daily. As an internal tooling team, engineers are expected to directly interact with customers to develop requirements and design, release and maintain distributed systems with visibility throughout Salesforce.

This is a fantastic opportunity for someone who is passionate about building scalable, resilient, distributed systems that collect, process, and analyze massive volumes of operational data. The technology stack includes Spark, Hive, Presto, Airflow, Docker, Postgres, and microservices with opportunities to work in cloud native environments.

We are looking for a Senior Engineer who can drive our strategy for optimizing cost efficiency and improving utilization across all of the Salesforce services. You will not only provide visibility into opportunities to reduce cost, but also work with multiple service owners to help and guide delivering on those optimizations.

Your Responsibilities:

• Drive cost optimization improvements across multiple services at Salesforce

• Lead data pipeline and application development being delivered by multiple engineers

• Lead and participate in requirement gathering, design, and development of complex datasets

• Independently design and deliver analytics tools and frameworks for diverse users, including other data engineers, data scientists, and domain experts

• Mentor team members in all aspects of the data maturity lifecycle

• Master our data management process, data culture, and code base, then improve it

• Build resilient, automated systems and assessing and integrating best-in-class technologies when appropriate

Required Skills:

• Bachelors degree in Computer Science and 12+ years of experience, or equivalent industry experience

• Deep knowledge of two or more functional or scripting programming languages: Java, Python, Scala, or R

• Extensive experience with distributed SQL analytics (Spark/Hive/Presto), relational databases (Postgres or similar) and ETL pipeline

• Experience with orchestration and workflow management tools: Airflow

• Experience with Agile development methodology, Test-Driven Development, incremental delivery, and CI/CD

• Experience owning and operating services throughout the software development lifecycle including design, development, release and maintenance.

• Deep knowledge of distributed services (REST, RPC or similar) and relational databases (Postgres or similar)

• Experience communicating technical vision, mentoring junior engineers and managing projects.

• Experienced in infrastructure automation and cloud platforms: AWS, Azure, or GCP

Desired Skills/Experience:

Specialization in one of the following areas:

• Understanding of Data Science/Machine Learning concepts, experience working with Data Scientists and operating ML models in production services

• Experience in FinOps domain