高级数据工程师 – 临床平台 (Databricks)
Senior Data Engineer – Clinical Platforms (Databricks)
🚀 加入我们的远程数据产品与机器学习初创公司！ 🚀
在 Muttdata，我们构建创新的数据产品和机器学习解决方案，帮助公司解决复杂的业务挑战。作为一家快速发展的远程优先的初创公司，我们对技术、协作和持续学习充满热情。
我们正在寻找一位经验丰富的、以结果为导向的高级数据工程师加入我们的团队 🐶🚀。你将负责下一代内部临床试验软件平台的架构、设计和实现，该平台直接基于 Databricks 构建，弥合软件开发与大规模数据工程之间的差距。
此职位需要与前端开发人员、软件架构师、临床研究团队以及临床 QA 和验证团队紧密合作。需要具备扎实的 Databricks 实操经验和对临床数据标准及受监管环境的深刻理解。在快节奏、协作的环境中，拥有责任感、清晰的沟通能力以及构建稳健、合规且可扩展解决方案的能力至关重要。
🚀 我们的工作内容
- 利用我们的专业知识，为需求规划和预算预测构建现代机器学习系统。
- 开发可扩展的数据基础设施，提升针对每个客户的高层决策能力。
- 提供全面的数据工程和定制 AI 解决方案，优化基于云的系统。
- 使用生成式 AI，帮助电商平 台和零售商更快地创建更高质量的广告。
- 构建深度学习模型，增强各行业的视觉识别和自动化能力，提高产品分类、质量控制和信息检索。
- 开发推荐模型，为电商、流媒体和数字平台提供个性化用户体验，提升参与度和转化率。
🌟 我们的合作伙伴
- 亚马逊网络服务
- Astronomer
- Databricks
🌟 我们的价值观
- 📊 我们是数据极客
- 🤗 我们是开放的团队合作者
- 🚀 我们承担责任
- 🌟 我们有积极的心态
🔍 想了解我们正在做什么？查看我们的案例研究，并深入阅读我们的博客文章，了解更多关于我们的文化以及我们正在开展的令人兴奋的项目！ 🚀
职责 🤓
- 使用 Databricks（PySpark、Spark SQL、Delta Lake）设计、构建和优化企业级数据流水线、数据湖存储层和数据模型，以支持定制的临床应用后端。
- 与前端开发人员、软件架构师以及...
查看英文原文
🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀
At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.
We are looking for an experienced, ownership-driven Senior Data Engineer to join our team 🐶🚀. You'll lead the architecture, design, and implementation of a next-generation, in-house clinical trial software platform built directly on Databricks, bridging the gap between software development and large-scale data engineering.
This role works closely with frontend developers, software architects, clinical research teams, and Clinical QA and Validation teams. It requires solid hands-on experience with Databricks and a strong understanding of clinical data standards and regulated environments. Ownership, clear communication, and the ability to build robust, compliant, and scalable solutions are essential to succeed in this fast-paced, collaborative environment.
🚀 What We Do
- Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
- Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
- Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
- Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
- Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
- Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
- Amazon Web Services
- Astronomer
- Databricks
🌟 Our Values
- 📊 We are Data Nerds
- 🤗 We are Open Team Players
- 🚀 We Take Ownership
- 🌟 We Have a Positive Mindset
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀
Responsibilities 🤓
- Design, build, and optimize enterprise data pipelines, lakehouse storage layers, and data models using Databricks (PySpark, Spark SQL, Delta Lake) to power custom clinical application backends.
- Collaborate with frontend developers, software architects, and clinical research teams to build API-driven endpoints, data ingestion engines, and query layers for proprietary clinical trial software.
- Build performant, standards-compliant data structures to store EDC outputs, audit trails, device telemetry, and patient-reported outcomes, enabling rapid querying and downstream analytics.
- Partner with Clinical QA and Validation teams to ensure database structures, data pipelines, and clinical data repositories comply with GxP, 21 CFR Part 11, HIPAA, and GDPR.
- Implement real-time and batch ingestion jobs connecting legacy clinical systems, central labs, EHRs, and wearable devices into a unified Databricks Lakehouse architecture.
- Monitor, troubleshoot, and optimize Spark jobs, Delta Lake tables, and query execution times to support high-throughput, low-latency clinical platform workflows.
Required Skills 💻
- 4+ years of hands-on experience building production data pipelines and lakehouse architectures using Databricks, Delta Lake, and Apache Spark (PySpark or Scala).
- Demonstrated experience building, extending, or maintaining custom software applications for clinical trials (e.g., custom EDC, CTMS, Clinical Data Repositories, or eCOA/ePRO platforms).
- Deep understanding of clinical data standards and regulatory environments, including CDISC (SDTM, ADaM, CDASH), 21 CFR Part 11, GxP validation, and ICH-GCP guidelines.
- Strong experience with relational schema design, dimensional modeling, and unstructured data handling within Delta Lake environments.
- Proficiency in Python, SQL, RESTful API integrations, CI/CD pipelines, Git, and automated testing frameworks.
- Experience working in cloud environments (AWS preferred, Azure or GCP).
- Advanced English to discuss technical requirements and solutions with clients in the United States
Nice to have 💻
- Bachelor's or Master's degree in Computer Science, Data Engineering, Bioinformatics, or a related quantitative field.
- Experience with Databricks Workflows, Delta Live Tables (DLT), and Unity Catalog governance.
- Background working in a validated system environment (Computer System Validation / CSV).
🎁 Perks
- Remote-first culture – work from anywhere! 🌍
- AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- In-Company English Lessons.
- Birthday off + an extra vacation week (Mutt Week! 🏖️)
- Referral bonuses – help us grow the team & get rewarded!
- Maslow: Monthly credits to spend in our benefits marketplace.
- ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
- 👶 Monthly Childcare Reimbursement – Because supporting families matters too