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Senior Data Engineer at Rezilient Health. At Rezilient, we’re redefining primary care by making access to healthcare more convenient, timely, and seamless. Our innovative CloudClinic model combines virtual provider visits with cutting-edge technology to create a personalized digital healthcare experience that puts patients at the center of their care. By streamlining care delivery and continuously expanding specialty services, we empower our care team to focus on patient well-being while providing the most comprehensive and accessible care possible.. Rezilient Health is seeking a skilled, detail-oriented Data Engineer to architect and run the data backbone behind our mission. You’ll partner with operations, clinical, and engineering leaders to turn fragmented healthcare data into trustworthy, near-real-time insights that shorten time-to-care and keep patients at the center. You’ll design scalable batch and streaming pipelines into a secure, compliant data platform, model reliable core domains, and publish well-documented datasets that power patient and provider experiences. Your work will enable cutting-edge analytics and  reporting, directly improving our care delivery and operational efficiency.. Key Responsibilities:. Design, build, and maintain data pipelines that ingest, process, and transform data from various sources, including clinical operations, patient interactions, and system performance.. Collaborate with data scientists, analysts, and business stakeholders to understand requirements and enable  reliable, data-driven product features and insights. Develop and manage the data infrastructure, including databases, data lakes, warehouses, and ETL processes.. Optimize query performance and storage strategies to handle large, complex datasets. Ensure data integrity, accuracy, and security across all stages of the data lifecycle, and support compliance with healthcare regulations (e.g., HIPAA).. Implement best practices in data modeling, database design, and data architecture to support robust analytics and reporting capabilities, as well as downstream ML / AI applications.. Create and maintain documentation for data engineering processes and pipelines.. Stay current with industry best practices and emerging technologies in data engineering and architecture.. Required Qualifications:. Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. . 3+ years of experience in data engineering, analytics, or a related role.. Strong proficiency in SQL and experience working with large-scale databases and data warehouses.. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and data warehouse solutions (e.g., Redshift, BigQuery, Snowflake).. Proficiency in programming languages such as Python or Scala for data processing and analysis.. Familiarity with ETL frameworks and tools like Apache Airflow, dbt, or similar.. Strong understanding of data governance, data quality, and healthcare compliance and security best practices.. Ability to work cross-functionally and communicate technical concepts to non-technical stakeholders.. Preferred Qualifications:. Experience in the healthcare industry or working with healthcare-related datasets (e.g., clinical and/or claims data) and data interchange standards (e.g., HL7, FHIR, X12). Familiarity with machine learning techniques and tools for predictive analytics.. Company Location: United States.