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.