Senior Data Engineer

• 5+ years of experience in Data engineer role




• Strong and proficient in Python, with the ability to mentor and assist the team in solving complex Python-related queries




• Experience in data visualization for complex datasets, especially of large-scale datasets and time series data, with a strong understanding of tools and techniques such as Power BI




• Expertise in SQL, PySpark, and Dask for data engineering and analysis




• Proficiency in working with relational and cloud databases, including PostgreSQL and Redshift




• Familiarity with cloud technologies (AWS, Snowflake)




• Experience in multimodal time-series data (e.g., Accelerometer, ECG, PPG, EEG, etc.) from biosensors




• Excellent communication skills for collaborating and presenting technical concepts



• At least an Upper-Intermediate level of English
  
  

• Design, build, and maintain data pipelines, ensuring seamless integration and high-performance processing of large-scale datasets




• Design and build dashboards to present complex datasets to our stakeholders using PowerBI




• Provide Python expertise, supporting team members with queries and troubleshooting, while driving best practices in code quality and development




• Communicate results through reports, presentations, and documentation

Will be a plus:

• Familiarity with LLMs and drive technical innovation by implementing generative AI technologies such as RAG (Retrieval-Augmented Generation) and exploring applications in digital health data




• Knowledge of GPU computing, high-performance computing, and cloud-native applications




• Knowledge of containerization tools like Docker and their application in deploying data workflows




• Manage and optimize cloud infrastructure (AWS & snowflake), including databases, Kubernetes clusters, AWS Bedrock, Athena, and S3 integration




• Familiarity with cardiovascular, neuroscience, or epidemiology data




• Experience in FDA submissions, validation, and working within GxP environments