Databricks 前置部署工程师（AI/ML）
Databricks Forward Deployed Engineer (AI/ML)
合作类型：独立承包商（1099）
主要联系人：产品经理和实践负责人
地点：远程（拉美地区）
在 RevStar，我们构建前沿的云、数据和生成式 AI 解决方案，改变企业组织的运作方式。作为 AWS 和 Databricks 生态系统中的战略合作伙伴，我们不仅仅是交付代码——我们解决复杂业务问题，现代化遗留数据体系，并部署可投入生产的 AI 应用程序，以推动实际业务价值。
我们的核心价值观：
- 自我精进：我们对思考、沟通和提升的标准很高。
- 主动负责：我们对结果负责，而不仅仅是努力。
- 共同命运：我们共同成功或失败。
职位概述
我们正在寻找一位高级 Databricks 前置部署工程师（FDE）加入我们不断壮大的数据与 AI 实践团队。在这个高度可见的职位中，你将直接嵌入技术架构、实际工程和高管客户参与的交汇点。
作为 FDE，你既是资深建造者，也是值得信赖的技术顾问。你将负责高影响力企业客户的完整交付生命周期——设计可扩展的数据基础架构，实施前沿的生成式 AI 解决方案，并将复杂的工作负载迁移到 Databricks Lakehouse 平台。同时，你将通过识别新的用例并与客户技术领导层建立战略共识，推动客户采用和使用增长。
主要职责
- 实战解决方案架构与工程：使用 Databricks 平台、Spark、Python/PySpark 和现代云生态系统（AWS/Azure/GCP）设计、构建和部署生产级数据管道、分析引擎和生成式 AI/大语言模型（LLM）应用程序。
- 企业客户交付：作为战略企业客户项目的主要技术负责人。与高管、数据部门副总裁/总监和工程团队合作，将业务挑战转化为高性能技术解决方案。
- Databricks 迁移与体系现代化：领导复杂遗留平台迁移（如 Snowflake、Teradata、旧版 Hadoop、SQL Server）到 Databricks Lakehouse 架构。
- 生成式 AI 与高级分析实施：指导企业客户（医疗保健、零售、金融服务等）采用生成式 AI 解决方案、RAG 架构、模型微调以及 MLflow/Databricks Mosaic AI 集成。
- 推动平台采用与增长：与客户方管理层合作，制定策略以促进平台的广泛采用和持续增长。
查看英文原文
Engagement Type: Independent Contractor (1099)
Primary Point of Contact: Product Manager and Practice Leader
Location: Remote (LATAM Based)
At RevStar, we build cutting-edge cloud, data, and Generative AI solutions that transform how enterprise organizations operate. As a strategic partner in the AWS and Databricks ecosystems, we don’t just deliver code—we solve complex business problems, modernize legacy data estates, and deploy production-grade AI applications that drive real business value.
Our Core Values:
- Self-Mastery: We hold a high bar for how we think, communicate, and improve.
- Ownership: We own outcomes, not just effort.
- Shared Destiny: We rise or fall together.
Role Overview
We are seeking a Senior Databricks Forward Deployed Engineer (FDE) to join our growing Data & AI Practice. In this highly visible role, you will work embedded directly at the intersection of technical architecture, hands-on engineering, and executive client engagement.
As an FDE, you are both a master builder and a trusted technical advisor. You will own the full delivery lifecycle for high-impact enterprise accounts—designing scalable data foundations, implementing cutting-edge Generative AI solutions, and migrating complex workloads onto the Databricks Lakehouse platform. Simultaneously, you will drive customer adoption and consumption growth by identifying new use cases and building strategic alignment with client technical leadership.
Key Responsibilities
- Hands-on Solution Architecture & Engineering: Design, build, and deploy production-grade data pipelines, analytics engines, and Generative AI/LLM applications using the Databricks platform, Spark, Python/PySpark, and modern cloud ecosystems (AWS/Azure/GCP).
- Enterprise Customer Delivery: Serve as the primary technical leader on strategic enterprise client engagements. Partner with C-level executives, VP/Directors of Data, and engineering teams to translate business challenges into high-performing technical solutions.
- Databricks Migration & Estate Modernization: Lead complex legacy platform migrations (e.g., Snowflake, Teradata, legacy Hadoop, SQL Server) onto the Databricks Lakehouse architecture.
- GenAI & Advanced Analytics Implementation: Guide enterprise customers (Healthcare, Retail, Financial Services, etc.) in adopting GenAI solutions, RAG architectures, model fine-tuning, and MLflow/Databricks Mosaic AI integrations.
- Drive Platform Adoption & Growth: Partner with account leadership to identify new, high-value technical use cases across client business units, expanding Databricks platform usage and driving measurable ROI for clients.
- Technical Mentorship & Practice Building: Mentor and coach junior Solution Engineers, Architects, and Consultants. Contribute to internal RevStar code libraries, reusable accelerators, and technical delivery best practices.
Requirements
Technical Expertise:
- 5+ years of hands-on experience in Data Engineering, Machine Learning, or Solutions Architecture.
- 3+ years of deep technical experience within the Databricks Ecosystem (Delta Lake, Unity Catalog, MLflow, Spark/PySpark, Databricks Workflows/Jobs, Mosaic AI).
- Generative AI / ML: Practical experience designing and deploying RAG pipelines, fine-tuning LLMs, working with vector databases, and managing ML pipelines end-to-end.
- Cloud Architecture: Strong expertise in cloud-native architectures (AWS preferred—S3, Glue, Lambda, Redshift, etc.).
- Data Migration: Proven track record of migrating enterprise legacy data warehouses/lakes onto Databricks.
- Databricks Certifications: Databricks Certified Data Engineer Professional and/or Machine Learning Professional preferred.
Client & Business Acumen:
- Enterprise Experience: Demonstrated track record of leading technical delivery for Fortune 500 or large enterprise clients (Healthcare, Retail, Consumer Goods experience is a strong plus).
- Consulting & Customer-Facing Skills: Exceptional verbal and written communication skills; comfortable presenting technical architecture, building POCs/demos, and managing client stakeholders up to the C-suite.
- Growth Mindset: Ability to spot technical expansion opportunities within existing client accounts and serve as a technical advocate to grow account footprint.
Benefits
Engagement Details & Terms
- Contract Status: Independent Contractor (Form 1099-NEC).
- Compensation: Hourly rate, commensurate with experience.
Originally posted on Himalayas