Lead Data Engineer

Tableau Software

United States

United States

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About

Salesforce is embarking on our own Digital Transformation to deliver customer success for our customers and accelerate our growth. A key pillar of this transformation is building a strong data foundation to support all of our core marketing needs through intelligent data sets as a service. We are seeking a seasoned and committed Lead AI Data Engineer to architect and build next-generation data pipelines and a central knowledge base for our Marketing organization at Salesforce. In this critical technical leadership role, you will work closely with business partners to translate complex sales and marketing needs into technical requirements, wrangle vast, real-time data from various systems, and design automated, large-scale pipelines. Your work will be instrumental in measuring the success of autonomous agents and enabling their global scale. This position requires an experienced professional who thrives in ambiguous, "0-to-1" environments and is passionate about building novel, high-impact AI systems. You will collaborate with internal technology groups to automate the entire data collection and definition process. Responsibilities AI/ML Systems at Scale: Design, build, and deploy production-grade AI/ML systems, with a preference for expertise in agentic systems, search/recommendation platforms, or data-intensive applications. LLM & Foundation Model Expertise: Extensive hands?on experience with LLMs, including fine?tuning, RAG, Context Engineering, Prompt Engineering, and deployment. Agent & Tooling: Develop systems enabling AI agents to reason, plan, and utilize external tools (APIs, databases). Technical Skills: Expert in Python and large?scale data processing technologies. Partner with marketing to define data requirements, build rapid POCs, and document specs. Automate ETL in Snowflake and Big Query. Construct DBT ETL pipelines for data ingestion and transformation. Implement GIT CI/CD for DevOps. Analyze metrics with business stakeholders to generate actionable insights. Develop POC solutions for new marketing metrics to aid decision?making. Design simple, repeatable, and reusable automation data frameworks. Oversee BI and data warehouse initiatives for Marketing. Review and validate designs against solution architecture and standards. Collaborate internally and externally on data collection, analysis, and reporting. Provide data support to Data Science teams for model production. Work effectively with global teams (North America, EMEA, APAC). Manage technical consultant(s).
Required Skills/Experience Minimum Qualifications
Bachelor's in Computer Science or related field with 10+ years of progressive experience in data engineering, modeling, automation, and analytics. Solid, hands?on expertise in AI/ML, specifically with Large Language Models (LLMs), including fine?tuning, RAG, Context Engineering, Prompt Engineering, and deployment. Robust understanding and clear articulation of data engineering principles, database design, tools, and architecture. Proven ability to manage multiple high?priority projects and meet deadlines. Proactive capacity to identify and implement operational improvements. Experience with Web analytics platforms and data sets (Google Analytics preferred). Proficient in Snowflake, Google Big Query, Redshift, or CDP. Solid experience with ETL technologies: DBT, IICS, and FiveTran. 10+ years of proficiency in SQL, Bash, and Python scripting. 7+ years of hands?on experience with Airflow, CI/CD (Jenkins/similar), and GitHub. Substantial experience with AWS technologies: ECS, CloudWatch, and Lambda. Prior experience mentoring junior team members in a customer?focused environment. Experience collaborating closely with Analytics/Data Science teams. Essential team?first mentality and excellent interpersonal skills. Must proactively communicate status, identify risks, and drive results with minimal supervision. Highly motivated self?starter, agile in adapting to shifting priorities, and a critical thinker for innovative solutions under stringent deadlines.
Preferred
Experience working with globally distributed engineering teams. Experience with data visualization tools (e.g., Tableau). Experience with Marketing technology.
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United States

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