Immediate Hiring For Data Engineer with Health-Care Experience

Key Responsibilities

• Data Pipeline Development:

  Design, implement, and optimize scalable data pipelines for extracting, transforming, and loading (ETL) healthcare data from various sources.

• Healthcare Data Integration:

  Work with sensitive healthcare datasets, ensuring compliance with industry standards such as FHIR, HL7, and Epic Clarity extracts.

• Workflow Orchestration:

  Utilize tools like Apache Airflow (or similar) to orchestrate and automate complex healthcare data workflows at scale.

• Cross-Functional Collaboration:

  Partner closely with data scientists, backend engineers, and stakeholders to integrate and support data systems across the organization.

• Technical Problem Solving:

  Tackle domain-specific challenges with innovative solutions that enhance the quality, accessibility, and usability of healthcare data to improve patient outcomes.

Minimum Qualifications

• Bachelors degree in Computer Science, Data Science, Engineering, or a related discipline.
• At least 4 years of hands-on experience in data engineering roles, with strong proficiency in Python and MongoDB.
• Proven experience in building and maintaining robust data pipelines using data from hospital EHR systems.
• Familiarity with data lakes and scalable data architecture principles for storing and managing large datasets.

Preferred Qualifications

• Experience with Microsoft Azure cloud services and tools for scalable data processing and storage.
• Strong understanding of data validation and quality assurance practices in healthcare data workflows.
• Familiarity with anomaly and outlier detection techniques in high-volume datasets.
• Proficiency in using Apache Spark or similar tools to analyze and query large-scale data.
• Experience developing and maintaining RESTful APIs to facilitate data integration and accessibility.