Senior Data Engineer (Healthcare Data & AI)

TL;DR

Senior Data Engineer (Healthcare Data & AI): Building healthcare data engineering pipelines and analytics workflows for physiological, medical device, and EMR datasets with an accent on data quality, ETL/validation, and AI/ML model enablement. Focus on designing scalable transformations in AWS (S3/Athena/SageMaker), troubleshooting data integrity issues, and validating predictive outputs against statistical analyses.

Company

hirify.global is an independent technology consulting firm delivering guidance and solutions to businesses.

What you will do

• Retrieve, explore, and analyze large-scale datasets in Amazon S3 using AWS Athena and Amazon SageMaker.
• Perform data wrangling: identify missing data, time synchronization issues, anomalies, and measurement artifacts.
• Transform and parse CSV/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 and integrity issues using Athena, SageMaker, and Jupyter Notebooks; troubleshoot data transfer/collection problems with biomedical and IT stakeholders.
• Support predictive analytics and AI/ML development by analyzing physiological/vital sign/EMR data and validating outputs against SAS analyses; simulate retrospective healthcare datasets to test surveillance algorithms.

Requirements

• 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, especially Amazon S3, AWS Athena, and Amazon SageMaker.
• Experience with Jupyter Notebooks and strong understanding of ETL, data transformation, and data validation.
• Experience with structured and semi-structured data formats (CSV and XML) and with SQL on large datasets.
• On-site work in Cambridge, Massachusetts, USA.

Nice to have

• Experience with InfluxDB or other time-series databases.
• Knowledge of AI/ML workflows and predictive analytics.
• Experience with physiological/medical device/EMR data and familiarity with SAS and statistical validation processes.
• Experience in healthcare, medical technology, or life sciences; exposure to biomedical data analysis or clinical data environments.

Culture & Benefits

• International community with 110+ nationalities.
• Trust-focused environment; many leaders started at entry level.
• Training system with an internal Academy and 250+ modules.
• Dynamic work environment with internal events (afterworks, team buildings, etc.).

Hiring process

• Brief virtual/phone call to understand motivations and fit.
• Interviews (average 3) with team members and discussion of role expectations.
• Case study/test may be required depending on the position.

Location: Cambridge, Massachusetts, USA (On-site)