About this role
🚀 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 (https://blog.muttdata.ai/tag/Case%20Studies/1) case studies and dive into ourblog post (https://blog.muttdata.ai/) 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).
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 (https://maslow.hr/): Monthly credits to spend in our benefits marketplace.
- ✈️ 🏝️Annual Mutters' Trip (https://www.youtube.com/watch?v=dq1x2krHGb8&t=2s) – an unforgettable getaway with the team!
- 👶 Monthly Childcare Reimbursement – Because supporting families matters too