数据与AI工程师
Data & AI Engineer
在RevStar打造有意义的事物
- 职位名称：数据与AI工程师（Databricks专家）
- 汇报对象：数据与AI实践负责人
- 工作地点：远程（以美国为基础，优先考虑东部或中部时区）
- 就业类型：合同制
是否准备好在AI和大数据的前沿构建全新的Lakehouse解决方案？RevStar是一家创新公司，是官方的Databricks合作伙伴，正在启动一个独立的、跨云的数据、机器学习和AI实践。厌倦了在漫长的公司审批流程中耗费数月时间，最终却无法将AI概念投入生产？我们通过快速执行周期，将现代Lakehouse架构和生产AI转化为可扩展的企业解决方案。我们行动迅速，打破官僚主义，为重视实际工程影响的客户创始人和技术领导者交付生产就绪的解决方案。在这个职位中，你将直接与数据架构师、科学家和客户领导合作，将复杂的数据转化为可扩展的、生产就绪的AI模型。最重要的是，我们的团队遵循三个核心原则：
- 自我精进：我们对思考、沟通和改进的方式有高标准。
- 责任感：我们关注结果，而不仅仅是努力。
- 共同命运：我们共同成功或失败。
你的核心职责
1. Databricks Lakehouse与流水线工程：使用Apache Spark和Delta Lake在多云环境（AWS、Azure、GCP）中设计、构建和优化可扩展的ETL/ELT流水线。实现稳健的Lakehouse架构，无缝处理结构化和非结构化数据，满足企业级需求。自动化数据摄入、存储和特征工程工作流，以支持下游分析和实时AI工作负载。
2. 性能调优与MLOps集成：针对客户端环境中的Spark作业进行精细调优，实现低延迟、高吞吐量和最大化的云成本效率。与机器学习工程师和数据科学家合作，在Databricks中使用MLflow进行跟踪、版本控制和部署，实现AI模型的运维。使用CI/CD流水线和基础设施即代码（Terraform、Databricks CLI）建立自动化、生产级别的部署。
3. 数据治理与客户领导力：在Unity Catalog和云生态系统中实施企业级数据安全、访问控制和合规标准（GDPR、HIPAA、SOC 2）。直接与客户技术领导者、产品经理和工程团队合作，将复杂的AI数据需求转化为清晰的业务成果。撰写清晰的技术文档
查看英文原文
Build What Matters at RevStar
- Role Title: Data & AI Engineer (Databricks Specialist)
- Reports To: Data & AI Practice Lead
- Location: Remote (US-Based / Eastern or Central Time Zone Preferred)
- Employment Type: Full-Time W2
Ready to build greenfield Lakehouse solutions at the bleeding edge of AI and big data? RevStar is an innovation shop and official Databricks Partner launching a dedicated, cloud-agnostic Data, ML, and AI practice. Tired of spending months in endless corporate approval loops only to build AI concepts that never reach production? We turn modern Lakehouse architectures and production AI into live, scalable enterprise solutions in fast-paced execution cycles. We build fast, cut bureaucratic red tape, and ship production-ready solutions for client founders and tech leaders who value real engineering impact. In this role, you will work directly with data architects, scientists, and client leaders to turn complex data into scalable, production-ready AI models. Above all, our team operates on three core principles:
- 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.
Your Impact Pillars
1. Databricks Lakehouse & Pipeline Engineering: Design, build, and optimize scalable ETL/ELT pipelines using Apache Spark and Delta Lake across multi-cloud environments (AWS, Azure, GCP). Implement robust Lakehouse architectures that seamlessly process both structured and unstructured data at enterprise scale. Automate data ingestion, storage, and feature engineering workflows to support downstream analytics and real-time AI workloads.
2. Performance Tuning & MLOps Integration: Fine-tune Spark jobs for low latency, high throughput, and maximum cloud cost-efficiency across client environments. Partner with ML engineers and data scientists to operationalize AI models inside Databricks using MLflow for tracking, versioning, and deployment. Implement robust CI/CD pipelines and Infrastructure-as-Code (Terraform, Databricks CLI) to establish automated, production-grade deployments.
3. Data Governance & Client Leadership: Enforce enterprise data security, access controls, and compliance standards (GDPR, HIPAA, SOC 2) within Unity Catalog and cloud ecosystems. Collaborate directly with client tech leaders, product managers, and engineering teams to translate complex AI data requirements into clear business outcomes. Author clean technical documentation and lead seamless solution handoffs to client engineering teams upon project completion.
Requirements
What You Bring
- Core Experience: 3+ years in cloud-native data engineering with 2+ years of dedicated, hands-on Databricks, Apache Spark, Delta Lake, and MLflow experience.
- Technical Mastery: High proficiency in Python, SQL, Spark frameworks, CI/CD, and Infrastructure-as-Code (Terraform or Databricks CLI).
- Strong Differentiator: Active Databricks Certified Data Engineer (Associate or Professional) or Databricks ML Professional certification is strongly preferred and will set your application apart.
- Consulting Mindset: Proven track record operating in fast-paced Agile/DevOps consulting environments, delivering cloud-agnostic architectures with exceptional client communication.
Benefits
- Paid Time Off – Take the time you need to recharge and stay productive.
- Remote-First Working Environment – Collaborate from anywhere while staying connected with our global team.
- Comprehensive Health Coverage – Medical, Dental, Vision
- 401(k) Retirement Plan – Plan for your future with access to a company-sponsored 401(k) program.
- Annual Learning & Development Stipend – Invest in your skills with conferences, certifications, or courses.
- Peer Mentorship & Coaching – Learn from experienced engineers, product managers, and architects to accelerate your growth.
- Professional Growth Opportunities – Exposure to cutting-edge AWS GenAI, data, and cloud technologies across diverse industries.
- Company Outings & Volunteer Opportunities – Build relationships and give back to the community.
- Collaborative, Innovative Culture – Work alongside top talent in a fast-paced, supportive environment that values curiosity and initiative.
Equal Opportunity Employment
At RevStar, we don’t just accept differences — we celebrate them, we support them, and we thrive on them for the benefit of our employees, our customers, and our community. RevStar is proud to be an equal opportunity workplace.
Reasonable Accommodations
RevStar is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. To request reasonable accommodation, contact HR at .
Originally posted on Himalayas