About Us:

At Ciitizen, we have a singular mission: to improve the lives of the 350 million+ people suffering from rare and complex conditions. We empower patients with seamless access and control over their health data that they can share across our multi-sided platform with caregivers, providers and researchers to illuminate better treatment and support options, while bringing therapies to patients faster. We support tens of thousands of patients, work with a rapidly growing network of patient advocacy organizations, and innovate with leading biopharma organizations to accelerate therapies, always ensuring patients remain at the center.

We are a team of patients, caregivers, researchers and builders who have had first-hand experience across the spectrum of rare disease. Led by a seasoned founding team with a history of successful exits in healthcare and consumer startups, and supported by top-tier investors, we are a close-knit, mission-driven group seeking exceptional talents to join us.

We are a hybrid team based out of the San Francisco Bay Area.

Project Summary:

We are in search of a seasoned Analytics Engineer to enhance and re-architect our end-to-end analytics infrastructure. Our goal is to consolidate and streamline our data architecture and tooling, which includes marketing applications such as Wordpress, HubSpot, Salesforce, Amplitude, as well as customer and internal facing react applications, and an underlying LLM data platform used to extract clinical insights from medical records. This initiative is key to improving our data management, analytics capabilities, and ensuring compliance with HIPAA and other applicable privacy standards. Your role will encompass the full lifecycle of this project, from initial design to deployment. You will collaborate with internal teams to ensure that the system aligns with our operational needs and drives efficiency and insights across the organization.

Key Responsibilities:

  • Architect and implement a scalable and efficient end-to-end tracking system across our platform.
  • Conduct thorough analysis to understand and document data requirements.
  • Provide recommendations on best technologies and tooling.
  • Enhancement of AWS Instance: Augment and refine our current Amazon RDS for PostgreSQL setup to manage a wider array of data more effectively.
  • Data Integration: Seamlessly integrate data from HubSpot, Salesforce, and Snowflake, ensuring data integrity and fluidity.
  • Unique Identifier Implementation: Develop and institute a unique identifier for each customer to facilitate consistent tracking across different systems.
  • Compliance with privacy regulations: Strictly adhere to HIPAA and other applicable privacy regulations, especially critical due to the involvement of medical records and collection of health and health-relevant information from users via web and product interactions.
  • Develop data models, data pipelines, and ETL processes.
  • Ensure data integrity and optimize data processing workflows.

Qualifications:

  • Advanced degree in Computer Science, Engineering, or related field.
  • 5+ years experience in Data Engineering, particularly in tracking systems.
  • Proficient in SQL/NoSQL databases, Big Data technologies, and cloud platforms.
  • Expertise in Python, Java, Scala, or similar programming languages.
  • Demonstrated ability in data modeling, warehousing, and pipeline development.
  • Excellent problem-solving, analytical, and consulting skills.
  • Strong communication skills, with the ability to liaise effectively with various stakeholders.

Consultancy Terms:

  • Project-based contract with potential for extension.
  • Competitive consultancy fee, negotiable based on experience and expertise.
  • Flexible working arrangements, with potential for on-site visits.We welcome examples of previous projects where you have successfully enhanced and integrated data warehouse systems, particularly in the healthcare sector or related fields.
  • Client references or testimonials, especially from the healthcare industry, would be highly appreciated.