Description
Salesforce is looking for an exceptional Data Engineer to join our Data & Analytics organization and help power the future of intelligent, agentic Customer Success. In this high-impact role as a senior technical individual contributor, you will bridge the gap between raw data systems and the agentic layer driving true business impact.
Position Overview
You will architect, build, and scale the foundational data pipelines and data graphs that ground our AI agents in accurate, real-time, high-context data. By ensuring absolute data quality, reliability, and freshness, and partnering across engineering, data science, and product teams, you will create the unified data backbone that powers Agentforce's personalized, intelligent customer interactions.
Responsibilities
- Data Architecture & Development: Build the data architecture and catalog for AI consumption and human augmentation, leading with precision, rigor, and scale.
- Customer Graphs & Identity: Build on top of identity graphs, overlaying structured, unstructured, and real-time insights to power agentic systems and human-facing applications.
- Operational Excellence: Establish and enforce rigorous technical standards for data quality, latency, and index freshness, ensuring AI agents provide reliable, real-time insights.
- Cross-Functional Collaboration: Partner with engineering leaders, product managers, decision scientists, and data scientists to translate complex business needs into scalable, production-ready solutions.
- AI Integration & Automation: Lead high-impact initiatives to automate data delivery pipelines, ensuring seamless integration across internal databases, third-party APIs, and the AI orchestration layer.
- Software Engineering: Build and ship high-quality, production-grade software using modern engineering practices, embedding AI tools into your daily workflow to deliver secure, optimized code.
- Code Quality Assurance: Critically evaluate both human and AI-generated code for correctness, quality, security, and performance.
- On-Call Support: Participate in the team's on-call rotation to triage production data issues in real time, keeping critical services highly available.
Requirements
- Experience: 6+ years of experience as a Data Engineer or in a closely related technical role.
- Data Architecture & Orchestration: Proficiency in data modeling, data graphs, and building robust ETL/ELT pipelines to ingest and transform heterogeneous data sources using tools like Airflow and dbt.
- Graph Databases: Practical experience designing, querying, and managing graph databases (e.g., Neo4j, AWS Neptune) to support highly interconnected data structures and knowledge graphs.
- Technical Stack: Strong command of core data engineering tools and languages, specifically Python, SQL, and Spark.
- Cloud & Warehousing: Hands-on experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and modern cloud data warehousing solutions like Snowflake.
- Problem-Solving: Proven ability to troubleshoot and resolve complex, production-level data issues.
- Collaboration: Excellent communication skills and a proven ability to collaborate in a cross-functional environment.
Benefits
Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love.