Senior Data Architect

Senior Data Architect

Position Summary As a Senior Data Architect, you will shape the foundation of company's data ecosystem, driving innovative solutions that the company teams to unlock insights and achieve business goals. This role is pivotal in designing scalable, efficient data architectures while fostering collaboration and mentorship across teams. Join us in advancing our mission to create affordable, life-changing medications by leveraging data to make healthier, happier lives a reality.

Duties and Responsibilities Design, develop, and optimize data architectures and pipelines that align with Extract, Load, Transform (ELT)/Extract, Transform, Load (ETL) principles, ensuring scalability and business alignment. Solve complex data challenges to deliver actionable insights and create data products that enhance analytics and data science productivity. Mentor and advise teams on data standards, fostering a culture of collaboration, efficiency, and reusability in data and analytical solutions. Evaluate, implement, and deploy emerging data engineering tools and processes while partnering with technical teams to develop architectures for strategic enterprise initiatives. Ensure compliance with healthcare data regulations such as the Health Insurance Portability and Accountability Act, Protected Health Information, and Personally Identifiable Information. While performing the responsibilities of the job, the employee is required to talk and hear. The employee is often required to remain in a stationary position for a significant amount of the workday and frequently use their hands and fingers to handle or feel in order to access, input, and retrieve information from the computer and other office productivity devices. The employee is regularly required to move about the office and around the corporate campus. The employee is regularly required to stand, walk, reach with arms and hands, climb or balance, and to stoop, kneel, crouch or crawl.

Knowledge and Skills Proficiency in data lake architecture, big data development (e.g., Spark, Kafka), BI tools like Power Business Intelligence and Looker, and designing operational infrastructure for machine learning and advanced analytics. Key Competencies Customer Focus: Ability to build strong customer relationships and deliver customer centric solutions. Optimizes Work Processes: Know the most effective and efficient processes to get things done, with a focus on continuous improvement. Collaborates: Builds partnerships and works collaboratively with others to meet shared objectives. Resourcefulness: Secures and deploys resources effectively and efficiently. Manages Complexity: Makes sense of complex, high quality, and sometimes contradictory information to effectively solve problems. Ensures Accountability: Holds self and others accountable to meet commitments and objectives. Situational Adaptability: Adapts approach and demeanor in real time to match shifting demands of different situations. Communicates Effectively: Develops and delivers multi-mode communications that convey a clear understanding of the unique needs of different audiences. Values People: Our people define who we are as a company, and we believe that understanding and addressing the needs of our team, clients, and community is fundamental to fostering a culture of support and growth. Quality: Quality stands at the core of our mission, reflecting our commitment to excellence in every medication we produce. Service: We are here to serve others. Every interaction with our patients, providers, employees and other stakeholders comes from a place of service. Innovation: By continuously exploring new methodologies and embracing technology, we ensure that every solution we offer is at the forefront of pharmaceutical care.

Experience and Qualifications Minimum of 5 years of experience as a data architect in analytical and data sciences environments, including 5 years in data engineering or architectural roles. Master's degree in Computer Science or Computer Engineering with 10 years of experience, or a Bachelor's degree in Computer Science or Computer Engineering with 15 years of experience. Extensive expertise in Structured Query Language, Enterprise Data Warehouse, ELT/ETL, and data governance, with experience in programming languages (Python or Scala preferred) and database technologies such as Snowflake, BigQuery, relational, Not Only Structured Query Language, and cloud-based data platforms.