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Data Engineer

1 month ago

Tulsa, United States Laureate Institute for Brain Research Full time

Are you passionate about leveraging electronic health records (EHR) to drive groundbreaking research and improve data-driven decision-making? We are seeking a skilled and motivated EHR Data Engineer to join our team. In this role, you will play a pivotal part in advising on EHR data availability and interpretation, and in collaborating with researchers and data scientists to streamline data extraction and analysis processes. Your expertise will be crucial in designing and maintaining efficient data pipelines, ensuring data security and compliance, and delivering actionable insights through comprehensive reporting.


As the bridge between research teams and IT staff, you will manage data integration, quality assurance, and troubleshooting to support our research objectives and uphold institutional standards. With a focus on continuous improvement and stakeholder engagement, you will drive advancements in EHR data management while providing training and support to ensure effective use of data tools and methodologies. If you are ready to contribute to cutting-edge research and enhance data management practices, we invite you to apply and make a significant impact in this exciting role.


Key Responsibilities:

  1. Advise on EHR Data: Advise on the availability and interpretation of electronic health records (EHR) data to support research objectives.
  2. Collaborate with Researchers and Data Scientists: Collaborate with researchers and data scientists to develop specifications for data to be exported and analyzed.
  3. Pipeline Development: Design, develop, and maintain robust pipelines to ingest, clean, transform, and annotate large volumes of data from various sources, including EHR systems, using SQL and R/Python.
  4. Optimize Pipeline Performance: Optimize pipeline performance and scalability by developing efficient SQL queries.
  5. Data Security and Compliance: Ensure data security and compliance with relevant regulations and standards, including HIPAA.
  6. Documentation and Organization: Create and maintain documentation and organization of pipelines and datasets.
  7. Liaise with IT Staff: Act as the primary point of contact between the research team and IT staff to ensure accurate and timely data collection and clarification of clinical data points.
  8. Data Quality Assurance: Implement and manage processes to ensure the accuracy, completeness, and consistency of extracted data, including routine audits and validation checks.
  9. Troubleshooting and Problem Resolution: Identify and resolve technical issues related to data extraction and processing, working closely with IT and EHR system vendors as needed.
  10. Report Generation: Develop and generate regular reports and dashboards to provide insights into the data extraction process, data quality, and research findings.
  11. Documentation and Compliance: Ensure that all data extraction processes and protocols are thoroughly documented and comply with institutional policies, ethical guidelines, and regulatory requirements.
  12. Data Integration: Facilitate the integration of EHR data with other data sources, such as ACS data, to support comprehensive research analyses.
  13. Stakeholder Engagement: Engage with various stakeholders, including hospital administration, IT departments, and research teams, to align data extraction efforts with organizational goals and research objectives.
  14. Continuous Improvement: Stay updated with the latest developments in EHR technologies and data management practices, and continuously seek opportunities to enhance the data extraction and preparation process.
  15. Project Management: Manage timelines, deliverables, and resources for data extraction projects, ensuring that milestones are met and projects are delivered on time and within scope.
  16. Training and Support: Provide training and ongoing support to researchers and staff on the use of EHR data and tools, ensuring they understand data structures, extraction methods, and analytical capabilities.


Qualifications:

Educational Background:

  • Bachelor's Degree in Computer Science, Data Science, Health Informatics, Statistics, or a related field. A Master’s Degree in a relevant field is preferred.

Professional Experience:

  • Experience in working with electronic health records (EHR) systems and managing healthcare data.
  • Proven track record of designing and managing data pipelines using SQL and programming languages such as R or Python.
  • Experience with data integration and data quality assurance processes.

Technical Skills:

  • Proficiency in SQL for querying databases and optimizing performance.
  • Strong skills in data manipulation and analysis using tools such as R or Python.
  • Experience with data security practices and compliance with regulations like HIPAA.
  • Familiarity with EHR systems (e.g., Epic, Cerner) and other healthcare data sources.