Lead Data Engineer (Lead Member of Technical Staff)

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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.

• Data Architecture & Development: Architect, build, and scale the data architecture and catalog strategy for AI consumption and human augmentation, driving cross-team alignment and reviewing external designs to pioneer long-term technical evolution.
• Customer Graphs & Identity: Lead the design and implementation of complex enterprise identity graphs, integrating structured, unstructured, and real-time insights to power agentic systems and human-facing applications.
• Operational Excellence: Establish, govern, and enforce rigorous cross-team technical standards for data quality, latency, and index freshness, ensuring AI agents provide reliable, real-time insights across the platform.
• Cross-Functional Collaboration: Influence and partner with engineering leaders, product managers, decision scientists, and data scientists to align macro-level project roadmaps and translate business vision into production-ready technical solutions.
• AI Integration & Automation: Force multiply high-impact initiatives to automate platform-level data delivery pipelines, ensuring seamless, secure integration between internal databases, third-party APIs, and the AI orchestration layer.
• Software Engineering: Set the engineering standard for shipping robust, production-grade software; manage technical debt and define release planning strategy while evangelizing modern, AI-driven development workflows.
• Code Quality Assurance: Critically evaluate both human and AI-generated code for correctness, quality, security, and performance.
• On-Call Support: Provide technical oversight for the team's on-call architecture, serving as a primary escalation point to resolve complex, system-wide production data bottlenecks and ensure high availability.

• Experience: 8+ years of data engineering experience with a track record in cross-team technical leadership roles.
• Data Architecture: Advanced expertise in data modeling and architecting scalable ETL/ELT pipelines for complex, heterogeneous sources using Airflow and dbt.
• Graph Databases: Extensive experience designing, querying, and managing production-scale graph databases (e.g., Neo4j, AWS Neptune).
• Technical Stack: Master-level command of Python, SQL, and Spark, with proven success in performance tuning and cloud cost optimization at scale.
• Cloud Infrastructure: Hands-on experience architecting and scaling modern data systems within AWS, Azure, or Google Cloud, and enterprise data warehouses like Snowflake.
• Problem-Solving: Proven ability to triage, resolve, and structurally prevent system-wide architectural failures and data bottlenecks.
• Leadership & Communication: Exceptional ability to influence without authority, mentor engineers within the team, and translate technical concepts for business stakeholders.

• Salesforce Ecosystem: Hands-on experience with the Salesforce platform, specifically enterprise-level implementations of Salesforce Data Cloud.
• AI-First Engineering Mindset: A track record of pioneering an AI-first engineering culture and cultivating development workflows utilizing modern AI tools (e.g., Claude Code, GitHub Copilot, Cursor) to maximize organizational velocity.