Are you interested in building the future of healthcare and transforming the patient experience? Are you hopeful about what data and medical research can do to improve medicine? We’re looking for a Senior Data Engineer to ensure PatientIQ remains at the forefront of using data to drive positive healthcare outcomes.
As a core member of the Data Engineering department, you will be in a dynamic environment that works cross-functionally with all other departments, such as Engineering, Product, Customer Success, and Marketing. You will work on a broad array of problems that rely on data to derive insights for our business and customers. We heavily value diligence, curiosity, and initiative, which are key to unlocking the value of PatientIQ's data for our users and decision-making. Your work will be impactful across the entire organization.
Role Responsibilities
- Clean and process large, complex datasets using tools such as SQL and Python.
- Migrate client data into PatientIQ's platform per established service level agreements (SLA).
- Develop rigorous data quality assurance checks throughout the ETL process.
- Design, develop, maintain, and streamline scalable data pipelines to support healthcare data analysis.
- Work closely with data analysts to understand their data needs and develop solutions to meet those needs.
- Monitor and optimize the performance of data pipelines and systems.
- Collaborate with other teams to integrate data from multiple sources.
Ideal Qualifications
- BS/MS in Computer Science, Engineering, Mathematics, or a related field.
- 4+ years of experience as a Data Engineer.
- Experience designing, building, and maintaining ETL infrastructure in a production setting.
- Experience working with large, complex datasets.
- Deep knowledge of SQL and at least one programming language (e.g., Python, Java, Ruby, etc.).
- Experience with version control systems (e.g., Git) and writing reusable and extensible code.
- Highly self-motivated with strong analytical problem-solving skills and attention to detail.
Nice to Haves
- Experience working in Healthcare, Finance, or another regulated industry.
- Experience with workflow management systems such as Airflow.
- Experience with data transformation tools like dbt.
- Experience in machine learning and/or business intelligence.
- Experience with cloud technologies such as AWS, Google Cloud Platform, or Azure.