Senior Data Engineer (Remote) - Clinical Trial Software & Databricks

About Us

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.

🚀 What We Do

We specialize in:

• Leveraging Machine Learning systems for demand planning and budget forecasting.
• Developing scalable data infrastructures to enhance high-level decision-making for clients.
• Offering Data Engineering and custom AI solutions to optimize cloud-based systems.
• Using Generative AI to help e-commerce platforms and retailers create higher-quality ads, faster.
• Building deep learning models for visual recognition and automation in industries like product categorization, quality control, and information retrieval.
• Developing recommendation models to personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

🌟 Our Partnerships

We collaborate with:

• Amazon Web Services
• Astronomer
• Databricks

🤓 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 compliance 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).
• 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).