Summary

The ideal candidate will have a strong background in data engineering, with a focus on healthcare data systems and analytics. As a Healthcare Data Engineer, you will play a key role in designing, building, and maintaining data pipelines, data warehouses, and analytics platforms that support our healthcare software solutions.

Responsibilities

Bachelor's, Master's, or Ph.D. degree in computer science, engineering, statistics, or a related field.
Collaborate with cross-functional teams, including data scientists, software developers, and healthcare professionals, to understand data requirements and design scalable and efficient data solutions.
Design, develop, and maintain data pipelines and ETL (Extract, Transform, Load) processes to ingest, process, and transform healthcare data from diverse sources, including electronic health records (EHRs), medical imaging data, wearable devices, and claims data.
Implement data integration and data modeling solutions to ensure the consistency, accuracy, and integrity of healthcare data across different systems and platforms.
Optimize data storage and retrieval mechanisms by designing and implementing data warehouses, data lakes, and data marts that meet the performance and scalability requirements of healthcare analytics applications.
Develop and maintain data quality and data governance frameworks to ensure the reliability, completeness, and security of healthcare data throughout its lifecycle.
Collaborate with DevOps engineers to automate deployment processes, manage infrastructure as code, and ensure high availability and reliability of data systems and platforms.
Implement data security and privacy measures to protect sensitive healthcare information (e.g., PHI) and ensure compliance with regulatory requirements, such as HIPAA and GDPR.
Perform data analysis, data profiling, and data visualization to identify trends, patterns, and insights in healthcare data and support data-driven decision-making.
Stay current with emerging technologies, trends, and best practices in data engineering, healthcare IT, and healthcare analytics, and apply this knowledge to improve our data solutions.
Document data architecture, data flows, and technical specifications, and provide training and support to internal stakeholders on data-related processes and tools.

Requirements

Strong proficiency in programming languages and scripting tools used in data engineering (e.g., Python, SQL, Scala).
Experience with big data technologies and frameworks, such as Hadoop, Spark, Kaka, and HDFS.
Solid understanding of data modeling concepts, relational databases (e.g., PostgreSQL, MySQL), and NoSQL databases (e.g., MongoDB, Cassandra, Melvus and Chroma).
Knowledge of data warehousing architectures, data integration techniques, and ETL tools (e.g., Informatica, Talend, Apache NiFi).
Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
Understanding of data security, privacy, and compliance requirements in healthcare IT, including HIPAA, GDPR, and HITRUST.
Excellent problem-solving skills, analytical thinking, and attention to detail, with the ability to troubleshoot complex data issues and propose effective solutions.
Strong communication skills, with the ability to collaborate effectively with cross-functional teams and communicate technical concepts to non-technical stakeholders.
Experience with healthcare interoperability standards and protocols, such as HL7 FHIR, DICOM, and CDA.
Knowledge of healthcare data exchange formats, including CCD, C-CDA, and Blue Buhon.
Previous experience working with healthcare data analytics tools and platforms (e.g., Tableau, Power BI, SAS).
Understanding of machine learning and artificial intelligence techniques for healthcare data analysis and predictive modeling.
Contributions to open-source projects, participation in technical communities, or attendance at healthcare IT conferences and events.