Director of Software Engineering (Data) at Salesforce in San Francisco, CA

Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. We’re hiring a Director of Software Engineering to lead our Data Engineering team. You’ll own the technical strategy and execution for enterprise-scale data ingestion platforms that power analytics, operational workflows, ML models, AI agents and business applications across the organization. This role will lead an established team of senior data engineers and drive the architecture of high-volume, high-throughput data ingestion systems. You’ll set engineering direction for data ingestion from 100+ enterprise systems into Snowflake and Data360 leveraging technologies like MuleSoft, Informatica, Spark, dbt, Iceberg, Kafka and Airflow while ensuring our data ingestion platform is scalable, reliable, governed, secure, and easy for internal teams to use. This is a director-level role with direct people management responsibility for senior data engineers. What You’ll Do Technical Leadership Define and execute the technical strategy and roadmap for enterprise data ingestion platforms. Architect, build, and operate high-volume, high-throughput batch and real-time data ingestion systems. Lead the design of scalable data pipelines and ETL/ELT workflows using technologies such as MuleSoft, Informatica, Spark, dbt, Iceberg, Kafka and Airflow. Design and optimize data models and storage architectures across Snowflake, Data360 and lakehouse environments. Partner with the Data Platform team to establish Apache Iceberg-based patterns for open, scalable, and interoperable data storage. Ensure data ingestion platforms meet enterprise requirements for availability, performance, security, observability, data quality, and disaster recovery. Drive platform scalability through automation, reusable frameworks, standardized ingestion patterns, and self-service capabilities. Establish and enforce engineering best practices, including architecture reviews, testing, code reviews, CI/CD, documentation, and operational readiness. Evaluate and champion new data technologies, frameworks, and architectural patterns. Maintain a strong balance between strategic technical leadership and hands-on involvement in critical architectural decisions. People Management Directly manage senior data engineers, providing mentorship, coaching, and career development support. Set clear goals and expectations, conduct regular one-on-one meetings, and lead performance and talent reviews. Build a collaborative, inclusive, accountable, and high-performing engineering culture. Develop technical leaders and create growth paths for senior and staff-level engineers. Partner with recruiting and engineering leadership to grow the team as business needs evolve. Establish effective team structures, ownership models, and operating mechanisms. Cross-Functional Collaboration Partner with Product, Data Platform, Architecture, Analytics, Data Science, Security, Governance, and business stakeholders to align priorities and technical direction. Translate complex business and data requirements into pragmatic technical strategies and execution plans. Represent Data Ingestion Platform in roadmap, investment, capacity-planning, and architecture discussions with senior leaders. Establish cl