Senior AI Data Engineer at Cortica

San Diego, California, United States -

Full Time

Start Date

Immediate

Expiry Date

11 Sep, 26

Salary

200000.0

Posted On

13 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, AWS, Azure, Data Pipeline Design, AI-First Development, Orchestration Frameworks, Application Development, Data Modeling, Dashboard Creation

Industry

Hospitals and Health Care

Description

Cortica is looking for a Senior AI Data Engineer to join its growing team! Cortica is a rapidly growing healthcare company pioneering the most effective treatment methods for children with neurodevelopmental differences. Our mission is to design and deliver life-changing care – one child, one family, one community at a time. Ultimately, we envision a world that cultivates the full potential of every child. At Cortica, every team member is instrumental in helping us achieve our mission! Our culture and values guide how we work and treat one another. Cortica celebrates diversity and fosters an inclusive environment, seeking ideas and opinions from everyone on the team. We safeguard equal rights and respect for all individuals, regardless of race, color, religion, sex, national origin, age, disability, creed, genetic information, sexual orientation, gender identity or expression, ancestry, veteran status or other applicable, legally protected characteristics. All Cortica employment decisions are made based on an individual’s qualifications and ability to successfully perform the job responsibilities. What will you do? The Senior AI Data Engineer will serve as both architect and builder of our data ecosystem. You’ll work closely with the data science, finance, and clinical operations teams to design intelligent, automated data solutions that power care decisions, financial planning, and operational efficiency. Own projects end-to-end: From stakeholder requirements through production deployment Design and build data pipelines that are reliable, scalable, and maintainable Develop and evolve data models that support clinical, financial, and operational reporting Use AI-assisted development as a core part of your daily workflow Build lightweight internal tools and dashboards where pipelines alone aren't enough Ensure data security and compliance across all work Collaborate across teams and document decisions so others can build on your work We’d love to hear from you if: You have 5+ years of experience designing and building production data pipelines. You bring 2+ years of experience working with AI-first development workflows. You're fluent in Python and SQL at an advanced level You bring 4+ years of experience with the following AWS and/or Azure big data services You have 2+ years of experience with orchestration frameworks You possess application development literacy to lightweight web tooling to complement data products. Your Compensation & Benefits Cortica cares deeply about the well-being of each member of our team, and we have created a passionate, caring, and growth-minded culture that helps teammates thrive! As a Cortica teammate, we’ll support your well-being through medical, dental, and vision insurance, a 401(k) plan with company matching and rapid vesting, paid holidays and wellness days, life insurance, disability insurance options, tuition reimbursements for professional development and continuing education, and referral bonuses. We value you and the experience you bring to your role, and are proud to provide you with a compensation and benefits package designed to enhance all aspectsof your life. The base pay range for this opening is $160,000 to $200,000. According to your skill level, relevant experience, education level, and location, you will receive compensation that fits appropriately within the range. EOE. This posting is not meant to be an exhaustive list of the role and its duties. #LI-NF1 #LI-Onsite

Responsibilities

The Senior AI Data Engineer will architect and build a data ecosystem to power care decisions, financial planning, and operational efficiency. This includes owning projects end-to-end, from designing scalable data pipelines to developing data models and internal tools.