The Salesforce Cloud Economics and Capacity Management (CECM) team is looking for a Lead Software Engineer with experience across distributed systems to join us!

Are you ready to apply Make sure you understand all the responsibilities and tasks associated with this role before proceeding. You will be working cross-functionally with engineers, FinOps analysts, and product managers to build the breakthrough features that our internal customers will love, adopt and use while ensuring stable and scalable applications. You'll be a part of a modern, lean, self-governing FinOps 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 financial operations (FinOps) decision-making pertaining to Salesforce infrastructure expenditure and capacity management. We are building a platform that provides near real-time monitoring of cloud cost and capacity utilization of the infrastructure, which will help in optimizing resource allocation, forecasting spend, and minimizing costs. We incorporate advanced machine learning techniques to turn the petabytes of data generated by our global infrastructure into actionable predictions and business insights used by FinOps practitioners, 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 cloud cost and usage data. The skillset requires strong data architecture, data processing, SQL and a proven track record working with enterprise metrics to build automated data pipelines. Broad experience in distributed backend development is preferred. Responsibilities Develop, automate, enhance, maintain scalable data pipelines

Independently design and develop resilient and reusable data automation frameworks

Lead distributed backend development pipeline development being delivered by multiple engineers (predominantly Python)

Automate cost anomaly detection, alerting, forecasting, budget process, and other FinOps capabilities

Develop and maintain dashboards and reports to visualize cloud cost and usage trends

Collaborate with finance and engineering teams to understand and manage cloud spending

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

Mentor team members in all aspects of the data maturity lifecycle

Work and collaborate with global teams across AMER and APAC regions

Required Skills/Experience Bachelor’s degree in Computer Science or equivalent industry experience

7+ years of experience in data engineering, preferably in cloud or FinOps environments

Experience in distributed computation such as Spark and Trino

Deep expertise in building data pipelines using tools like dbt, Airflow, and similar orchestration frameworks

Strong communication and stakeholder management skills

Experience working in Agile and Scrum methodology, incremental delivery, and CI/CD

Experience in at least one cloud service providers including AWS or GCP

Experience in distributed backend software engineering environments

Experience with data visualization tools, preferably Tableau

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