Senior Director of Engineering - Enterprise Data Platform (San Francisco)
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Job CategorySoftware 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. The Sr. Director of Engineering for the Enterprise Data Platform will provide unified technical leadership to modernize, integrate, and optimize Salesforce's enterprise data ecosystem. This foundational platform is crucial for enabling AI, analytics, and trusted self-service data access at scale. In this role, you will be at the forefront of driving interoperability across our technology stack, operationalizing a data mesh architecture, and ensuring our infrastructure is scalable, reliable, and cost-efficient. You will play a central part in aligning the platform's capabilities with strategic business priorities, including AI enablement, analytics modernization, and company-wide data democratization. Furthermore, you will lead the transformation of the developer experience by integrating next-generation AI-driven tools, such as Cursor for AI-powered coding and Model Context Protocol (MCP) for context-aware automation. By empowering our engineers with AI-assisted workflows, you will enable them to build faster, safer, and smarter. This position is pivotal in aligning our data and integration platform capabilities with Salesforce's strategic AI priorities. Key Responsibilities: Strategic Leadership
- Own the technical vision and roadmap for the Enterprise Data Platform Foundation.
- Align platform engineering priorities with company goals, including AI, analytics, and data-driven decision-making.
- Operationalize a data mesh architecture to enable domain-oriented ownership, interoperability, and AI/ML enablement.
- Champion the implementation of a unified governance and operating model across the Data Platform Foundation, which includes Salesforce Data Cloud, Snowflake, dbt Cloud, Airflow, Informatica, Tableau, and AWS.
- Redesign the developer journey to enhance speed, reliability, and simplicity, creating streamlined paths for data integration, analytics, and AI development.
- Integrate AI-assisted engineering practices (e.g., Cursor, MCP) into developer workflows to boost productivity, quality, and speed.
- Standardize pipelines, environments, and tooling to streamline deployments across multi-org and multi-cloud landscapes.
- Develop self-service capabilities while ensuring adherence to governance, security, and compliance standards.
- Lead platform engineering efforts to operationalize a data mesh architecture that supports domain-oriented ownership, interoperability, and self-service.
- Reduce technical debt and ensure consistent adherence to security and compliance standards.
- Drive automation, observability, quality, and standardization to improve uptime, performance, and cost efficiency.
- Implement platform reliability engineering practices to achieve industry-leading Service Level Agreements (SLAs).
- Oversee proactive incident management, performance optimization, and continuous improvement initiatives.
- Manage vendor relationships and optimize licensing, infrastructure, and operational spending.
- Build, lead, and mentor high-performing engineering teams across multiple disciplines.
- Foster a collaborative culture with strong cross-functional partnerships with Product, Security, Data Governance, and Business Units.
- 15+ years of experience in engineering leadership and portfolio/program management within the data and integration domain.
- Strong communication skills with the ability to influence both executive and technical audiences.
- A proven track record of delivering scalable, secure, and cost-optimized infrastructure solutions.
- Experience in enabling AI/ML and advanced analytics through data platform modernization.
- Deep expertise in technologies such as Snowflake, dbt Cloud, Airflow, Informatica IICS, Tableau, and Data Cloud.
- A proven track record of implementing AI-assisted developer tools (e.g., Cursor, MCP, Copilot).
- A strong background in platform operations, governance, and SLA management.
- Hands-on expertise with Apache Spark, Apache Iceberg, and Python for large-scale data processing and analytics.
- Experience delivering multi-million-dollar programs using Agile/SAFe methodologies.
- Exceptional ability to align technical execution with strategic business outcomes.
- Experience with cloud-native architectures (AWS, GCP, Azure) and hybrid deployments.
- A background in DevOps, MLOps, or DataOps practices.
- Familiarity with regulatory compliance (e.g., GDPR, SOX, CCPA) for enterprise data platforms.
- Demonstrated success in change management within a complex, matrixed organization.
- Accelerate AI innovation across the company on our Data Platform.
- Deliver a unified, governed, and cost-efficient platform.
- Ensure high availability, stability, and compliance through rigorous SLA management and governance.
- Empower developers and business units with faster, safer, self-service capabilities.
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