Principal Data Engineer

The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S., supporting 15,000 healthcare professionals and team members at more than 1,000 health and wellness offices across 46 states in four distinct categories: Dental Care, Urgent Care, Pet Care, and Medical Aesthetics. Working in partnership with independent practice owners and clinicians, the team is united by a single purpose: to prove that healthcare can be better and smarter for everyone. TAG provides a comprehensive suite of centralized business support services that power the impact of four consumer-facing businesses: Aspen Dental, ClearChoice Dental Implant Centers, WellNow Urgent Care, Lovet Veterinary Clinics and Chapter Aesthetic Studio. Each brand has access to a deep community of experts, tools and resources to grow their practices, and an unwavering commitment to delivering high-quality consumer healthcare experiences at scale.

Job Summary:

We are looking for a Principal Data Engineer to architect, build, and optimize scalable cloud-native data platforms that power business insights and decision-making. This role will lead the technical direction of our data engineering initiatives using DBT Cloud, Python, Airflow, and Google BigQuery while ensuring best practices in data modeling, pipeline orchestration, and platform scalability.

As a technical leader, you will mentor data engineers, drive engineering excellence, and collaborate with cross-functional teams to design and implement high-performance data solutions.

Key Responsibilities:

Data Platform Architecture & Development:

• Design, develop, and optimize scalable, cloud-native data platforms on Google Cloud (BigQuery, Cloud Storage, Pub/Sub, etc.).
• Lead the development of efficient ELT data pipelines using DBT Cloud, Python, and Airflow.
• Establish best practices for data modeling, performance tuning, and cost optimization in BigQuery.
• Design and implement data governance, security, and compliance frameworks.

Leadership & Mentorship:

• Act as a technical mentor for the data engineering team, providing guidance on architecture, code quality, and best practices.
• Drive engineering excellence by establishing and promoting CI/CD, infrastructure as code, and automation.
• Advocate for modern data engineering practices, including data observability and monitoring.

Collaboration & Strategy:

• Work closely with data analysts, data scientists, and business teams to translate business needs into scalable data solutions.
• Partner with ML and analytics teams to support real-time and batch data processing for AI-driven applications.
• Evaluate and implement emerging technologies to enhance platform scalability and efficiency.

Qualifications & Experience:

• 5+ years of experience in data engineering with a focus on cloud-native architectures.
• Strong expertise in DBT Cloud, Python, Airflow, and Google BigQuery.
• Hands-on experience designing scalable, cost-efficient data platforms in Google Cloud (GCP).
• Deep understanding of data warehousing, ELT architectures, and distributed computing.
• Experience with orchestration tools like Airflow and event-driven architectures.
• Strong knowledge of CI/CD, infrastructure as code (Terraform), and DevOps principles.
• Ability to lead teams, mentor engineers, and influence technical strategy.

Preferred Qualifications:

• Experience with streaming data pipelines (Kafka, Pub/Sub, Dataflow, etc.).
• Familiarity with data observability and monitoring tools (Monte Carlo).
• Knowledge of ML and AI data pipelines is a plus.

*This role is onsite 4 days/week in our Chicago office (Fulton Market District)

• A generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match
• Salary: $147,000 - 175,000/year