Senior Data Engineer supporting AI - enabled financial compliance initiative with data pipelines and ingestion processes. Collaborating with diverse teams in a mission - critical regulated environment.
About the role
- Data Engineer responsible for healthcare data infrastructure and collaborating with cross-functional teams. Translate requirements into data pipelines and ensure data quality and compliance.
Responsibilities
- 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.
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