Data Engineer at Helium Health

Role Overview

• As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure required to effectively collect, store, and analyze large volumes of healthcare data.
• You will collaborate with data scientists, software engineers, and healthcare professionals to develop scalable data pipelines and ensure data integrity, security, and accessibility.

As a Data Engineer, you will be required to:

• Translate business and functional requirements into robust, scalable, operable solutions that work well within the overall data architecture
• Design, implement, and maintain scalable ELT/ETL (Extract, Transform, Load) processes for healthcare data integration from various sources (e.g., EHR systems, clinical databases, third-party applications).
• Develop and optimize database architectures, including relational databases, data warehouses, and big data technologies (e.g., SQL, NoSQL, Hadoop).
• Ensure data quality, security, and compliance with healthcare regulations such as HIPAA.
• Collaborate with cross-functional teams (data scientists, software engineers, product managers) to design data models that support clinical decision-making and analytics.
• Build and manage data pipelines to ensure efficient data flow and real-time analytics.
• Implement data governance and master data management (MDM) strategies.
• Monitor and troubleshoot data pipelines and performance issues to ensure system reliability and uptime.
• Document data engineering processes, procedures, and data lineage for auditing and compliance purposes.
• Stay updated with industry trends and emerging technologies to recommend improvements for our data infrastructure.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field (Master’s degree preferred).
• 3+ years of experience in data engineering, ideally  in the healthcare or EHR domain.
• Strong experience with database technologies (e.g., MySQL, PostgreSQL, MongoDB, Redshift, Snowflake).
• Proficiency in ETL tools and frameworks (e.g., FiveTran, Dbt, MAGE, Prefect, Airflow).
• Expertise in programming languages such as Python, SQL, and Java/Scala.
• Familiarity with healthcare data standards and formats (e.g., HL7, FHIR, DICOM).
• Experience working with cloud platforms (e.g., AWS, Azure, GCP) and big data tools (e.g., Hadoop, Spark).
• Knowledge of healthcare regulations (e.g., HIPAA, GDPR) and data privacy best practices.
• Experience with data visualization and reporting tools (e.g. Power BI).
• Strong analytical skills and the ability to troubleshoot complex data problems.