Senior Data Engineer

We are looking for a Senior Data Engineer to join a multidisciplinary team focused on healthcare data engineering, analytics, and AI-driven solutions. In this role, you will work with large-scale physiological, medical device, and electronic medical record (EMR) datasets to support data quality, predictive modeling, and advanced analytics initiatives. You will collaborate with data scientists, software engineers, biomedical specialists, and IT teams to ensure reliable data pipelines, investigate data integrity issues, and contribute to the development and validation of machine learning models. Key Responsibilities Retrieve, explore, and analyze data stored in Amazon S3 using AWS Athena and Amazon SageMaker . Perform data wrangling by identifying missing data, time synchronization issues, anomalies, and measurement artifacts. Transform and parse CSV and XML datasets into scalable databases such as InfluxDB . Develop and maintain batch processing workflows using Python and Bash to inventory, process, and validate incoming device data. Investigate data quality issues through Athena , SageMaker , and Jupyter Notebooks to identify problems related to data curation, system configuration, storage, or performance. Troubleshoot data transfer and collection issues in collaboration with biomedical teams, IT stakeholders, and internal engineering teams. Analyze physiological, vital sign, and EMR datasets to support predictive analytics and AI/ML model development. Validate statistical and machine learning outputs by comparing Python-generated results with SAS analyses produced by biostatistics teams. Simulate retrospective healthcare datasets using a Virtual Hospital Simulator to evaluate and test surveillance algorithms. Contribute to continuous improvements in data engineering processes, data quality, and analytical workflows. Required Qualifications 7–10 years of experience in Data Engineering , Data Analytics, or a related technical field. Strong proficiency in Python for data processing and automation. Experience with AWS services, particularly Amazon S3 , Athena , and SageMaker . Experience working with Jupyter Notebooks . Solid understanding of ETL processes, data transformation, and data validation. Experience handling structured and semi-structured data formats, including CSV and XML . Familiarity with batch scripting using Bash . Strong analytical and troubleshooting skills with a focus on data quality and integrity. Experience working with SQL and large datasets. Excellent communication and collaboration skills in cross-functional environments. Nice to Have Experience with InfluxDB or other time-series databases. Knowledge of AI/ML workflows and predictive analytics. Experience working with physiological, medical device, or EMR data. Familiarity with SAS and statistical validation processes. Experience in the healthcare, medical technology, or life sciences industry. Exposure to biomedical data analysis or clinical data environments. Why choose us An international community bringing together more than 110 different nationalities An environment where trust is central: 70% of our leaders started their careers at the entry level A strong training system with our internal Academy and more than 250 modules available A dynamic work environment that frequently comes together for internal events (afterworks, team buildings, etc.) Amaris Consulting promotes equal opportunities. We are committed to bringing together people from diverse backgrounds and creating an inclusive work environment. In this regard, we welcome applications from all qualified individuals, regardless of sex, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or other characteristics. #J-18808-Ljbffr Amaris Consulting