Healthcare Data Engineer – AI/ML Enablement Specialist

2 days ago


Jaipur, Rajasthan, India beBeeData Full time ₹ 15,00,000 - ₹ 20,00,000
Job Description

We are seeking a seasoned data engineer to lead our AI/ML enablement initiatives in the healthcare sector. The ideal candidate will have extensive experience in designing, developing, and implementing advanced data solutions for complex healthcare datasets.

This role involves collaborating with cross-functional teams to deliver high-quality, compliant data pipelines for predictive analytics, risk stratification, fraud detection, and other use cases. You will be responsible for aggregating and consolidating large healthcare datasets from multiple systems, executing data extraction workflows, and conducting data quality assurance and validation checks.

The successful candidate will possess strong knowledge of healthcare standards and coding systems, including ICD-10, CPT, SNOMED, HL7, and FHIR. Proficiency in SQL, Python, and automation frameworks is also required. Additionally, experience integrating data from multiple healthcare systems and vendors, as well as cloud-based solutions such as Amazon Web Services (AWS), Microsoft Azure's healthcare cloud, and Google Cloud Healthcare, is essential.

Required Skills and Qualifications
  • Strong experience in healthcare data engineering, claims, EHR, and clinical datasets
  • Proficiency in data cleaning, normalization, aggregation, and feature extraction
  • Knowledge of healthcare standards and coding systems (ICD-10, CPT, SNOMED, HL7, FHIR)
  • Proficiency with SQL, Python, and automation frameworks for data workflows
  • Hands-on experience integrating data from multiple healthcare systems and vendors
Benefits

This role offers an exciting opportunity to work on complex AI projects that challenge and inspire. As part of our team, you will collaborate with experienced professionals who foster a nimble, client-focused environment that promotes delivery and professional growth.

Others

You will maintain thorough documentation of data processes, transformations, and metadata. Ensure compliance with HIPAA, data governance, and security standards. Develop and implement automation and scripting for efficient data handling. Take ownership of data quality assurance and validation checks to ensure reliability and accuracy.


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