Principal Observability Data Infrastructure Engineer

Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver.
 
Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.

CVS Health invites a seasoned and highly skilled Principal Observability Data Infrastructure Engineer to join our team. In this critical role, you will be the technical lead for development, management, and continuous refinement of our observability data platforms. This individual will be responsible for providing guidance to other engineers, and leading efforts with a hands-on approach to enhance data integrity and governance, optimize performance, streamline data processes, and broaden the scope of actionable insights derived from complex operational datasets. The ideal candidate is experienced in building and managing enterprise data pipelines and large-scale analytics architectures including Splunk, has experience establishing and enforcing processes and standards for data and platform/solutions governance, is proficient in query languages like SPL2, SQL, and has programming, source management, DevOps, and database management experience.

Key Responsibilities:

• Develop and implement advanced data collection, storage, and analysis solutions to support real-time monitoring and alerting.

• Implement and refine data models with a focus on bolstering data performance, reliability, and operational intelligence.

• Continuously improve our observability data platforms to meet evolving business needs and technological advancements.

• Enhance data integrity by establishing and enforcing robust data governance processes and standards.

• Work with our partners to drive value through actionable insights derived from operational datasets.

• Ensure compliance with industry regulations and internal policies regarding data security and privacy.

• Spearhead development of sophisticated data pipelines, utilizing an array of modern technologies to enable seamless data collection and near real-time data processing at massive scale.

• Optimize data flows, data tiering, classification, transformation, reduction, storage and retrieval strategies to ensure efficient data processing and delivery.

• Implement performance tuning and optimization techniques to maximize the efficiency and effectiveness of data infrastructure.

• Analyze, optimize, and report on resource utilization to minimize costs while maintaining high performance and reliability.

• Provide mentorship and guidance to other engineers, fostering a collaborative and innovative work environment.

• Lead cross-functional teams in the design, development, and deployment of observability solutions.

• Collaborate with stakeholders to understand their needs and translate them into technical requirements and solutions.

• Utilize proficiency in query languages like SPL2 and SQL to write and optimize complex queries for data extraction and manipulation.

• Apply programming skills and DevOps practices to automate workflows, manage source code, and ensure seamless integration and deployment of data solutions.

• Oversee data management and lifecycle activities, ensuring data consistency, security, and availability.

Required Skills and Qualifications:

• 10+ years of experience managing massive data platforms in a large enterprise, reflecting a deep understanding of observability, data pipelines, and analytics platforms in a complex ecosystem.

• Pipeline Mastery: 6+ years of mastery in crafting and maintaining high-volume data pipelines, with hands-on proficiency in industry-leading tools.

• Data Modeling: A deep understanding of contemporary data modeling techniques, data architecture strategies, and the intricacies of data platform architecture.

• Collaboration: A proven track record of effective cross-disciplinary collaboration, exhibiting the ability to meld technical prowess with business acumen.

• Problem-Solving: Exceptional problem-solving aptitude, adept at navigating the fast-paced challenges inherent in a dynamic healthcare IT environment.

• Communication: