The Advanced Analytics team at Blue Shield of California is seeking an Analytic Data Engineer to join us in transforming healthcare through innovation. We partner with a wide array of stakeholders to build impactful solutions for our members and providers. We are awed by the complex problems before us, and undaunted by the challenge. If there is data and a problem statement, we are building a solution.
This person will manage and optimizes production data pipelines supporting key data and analytics initiatives. You will be the cornerstone of a robust data stack, integrating diverse sources and serving up data to power machine learning solutions and self-service analytics. You will mine the operational details of adjudicating claims and build a real-time pipeline to feed an AI-enabled recommendation engine. You will follow our members’ journey through the healthcare landscape and blend data points across a broad spectrum of applications to create multidimensional records serving interventions. You will scrape surveys and munge data streams to extract measurable insights. From the minutiae of desk level procedures to macro population trends, there are no problems too big or small for your keen eyes and open mind.
- Build, develop, implement and execute extensible reusable data pipelines consisting of multiple acquisition sources and integration into use case driven endpoints.
- Maintain and optimize workloads in various deployment stages and data environments to ensure optimal performance as data volume and variety increase.
- Lead design activities in partnership with data scientists, analysts and product owners to translate functional requirements into technical specifications for scalable data pipelines.
- Oversee management of analytical data assets for exploratory and early stage analytic usage patterns, and develop recommendations to integrate with production pipelines.
- Collaborate with internal IT teams to troubleshoot incidents and coordinate resolutions to minimize disruption of analytic applications.
- Monitor data consumption patterns and develop enhancements to ensure pipelines adapt to evolving data schema and analytic use cases.
- Collaborate with data consumers to define and catalog use cases to ensure adherence to data governance standards and ethical/legal guidelines.
Knowledge and Experience
- A college degree or equivalent in computer science, data management, information systems or related quantitative field or 7 years of prior relevant experience.
- Requires five to 10 years’ experience in Health Care (managed care, academic, or gov't payer), Typically has 5 or more years’ experience as a Health Data Analyst, Health Data Management or Analytics.
- High proficiency working with large, heterogeneous datasets in building/optimizing data pipelines using ELT, data replication, API access, data virtualization, stream data integration, and emerging technologies.
- High proficiency with relational databases (Netezza, Oracle, MS SQL), NoSQL databases (MongoDB, Cassandra), and distributed computing platforms.
- Proficiency in Python, R, Scala, Julia or equivalent scripting language for data analysis.
- High proficiency with CI/CD tools and rigorous application of DataOps principles.
- Demonstrated ability to work across multiple deployment environments, operating systems and through containerization techniques such as Docker and Kubernetes.
- Ability to partner, collaborate with, and influence relevant stakeholders across diverse functions and experience levels.
- Strong independent judgment, critical thinking and problem-solving skills required to anticipate and respond to emerging challenges.