À propos de ce poste Senior Data Engineer – Clinical Platforms (Databricks) chez Muttdata
Muttdata · Télétravail · Remote
🚀 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
🌟 Our Partnerships
🌟 Our Values
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
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