Our client is a leading player in the healthcare industry, dedicated to improving patient care, optimizing healthcare processes, and driving data-driven decision-making. As a Data Engineer, you will play a critical role in our mission by designing, developing, and maintaining robust data infrastructure and systems to support our data-driven initiatives.
- Data Pipeline Development: Design, develop, and maintain scalable and efficient data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data from various sources, including electronic health records (EHR), claims data, medical devices, and other healthcare-related systems.
- Data Warehouse Design and Implementation: Architect, build, and optimize data warehouses and data marts to ensure efficient storage, retrieval, and analysis of healthcare data. Implement appropriate data models and schemas to support analytical and reporting needs.
- Data Integration: Collaborate with internal teams and external stakeholders to identify data integration requirements and implement data integration solutions. Ensure data quality and consistency across different data sources and systems.
- Data Transformation and ETL: Develop robust Extract, Transform, Load (ETL) processes and data transformation workflows to cleanse, standardize, and enrich data for analysis and reporting purposes. Apply best practices for data governance and data quality assurance.
- Performance Optimization: Monitor and optimize the performance of data pipelines, data warehouses, and ETL processes to ensure efficient data processing and timely availability of data for end-users. Identify and resolve performance bottlenecks and scalability issues.
- Data Security and Privacy: Implement appropriate data security measures and adhere to privacy regulations to protect sensitive healthcare data. Collaborate with the security team to establish data access controls, encryption mechanisms, and data anonymization techniques.
- Documentation and Collaboration: Create and maintain comprehensive technical documentation for data pipelines, data models, and ETL processes. Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and deliver optimal data solutions.
- Stay Up-to-Date with Emerging Technologies: Continuously research and evaluate emerging technologies, tools, and frameworks in the data engineering field. Identify opportunities to leverage new technologies for improving data processing, storage, and analysis capabilities.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer, preferably in the healthcare industry.
- Strong knowledge of database concepts, data modeling, and SQL.
- Proficiency in programming languages such as Python, Java, or Scala.
- Experience with big data processing frameworks like Apache Hadoop, Spark, or Kafka.
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
- Solid understanding of data integration techniques, ETL processes, and data governance.
- Knowledge of healthcare data standards, terminologies, and regulations (e.g., HL7, FHIR, HIPAA) is a plus.
- Experience with data visualization tools (e.g., Tableau, Power BI) is desirable.
- Excellent problem-solving, analytical thinking, and communication skills.
- Ability to work in a fast-paced environment and manage multiple priorities effectively.