The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S. and has supported over 20,000 healthcare professionals and team members with close to 1,500 health and wellness offices across 48 states in four distinct categories: dental care, urgent care, medical aesthetics, and animal health. 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 five consumer-facing businesses: Aspen Dental, ClearChoice Dental Implant Centers, WellNow Urgent Care, Chapter Aesthetic Studio, and Lovet. 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 Description
The Senior Data Engineer designs, builds, and operates data pipelines and platform infrastructure across multi-brand data platforms that power business insights and decision-making. This is a senior technical role driving data engineering initiatives using dbt Cloud, Python, Airflow, and Google BigQuery ensuring best practices in data modeling, pipeline orchestration, platform scalability, and data governance, while bringing modern AI-assisted engineering practices into the team's day-to-day work. The Senior Data Engineer will mentor other 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.)
- Establish best practices for data modeling, performance tuning, and cost optimization in BigQuery.
- Lead development of efficient ELT pipelines using dbt Cloud, Python, and Airflow
- Develop dbt models, tests, and documentation. Responsible to own data governance, data quality, security, and compliance standards across owned pipelines.
- Own feature delivery end-to-end, from design through production, including code review standards.
AI & Engineering Excellence
- Champion AI-assisted engineering (code review, documentation, data profiling) to boost team velocity and quality
- Build reusable tooling and playbooks that codify best practices for the broader team
- Evaluate and pilot emerging AI/LLM tools and workflows, recommending adoption where they improve engineering quality or speed
Reliability, Operations & Cloud
- Monitor and optimize BigQuery cost/performance, remediate anti-patterns (unclustered scans, credential misuse)
- Triage production issues quickly and consistently, participate in on-call and incident response, including PagerDuty-to-incident.io migration work
- Maintain observability (dashboards, alerting, freshness checks) and manage infrastructure as code (Terraform) for pipelines, DAGs, and Cloud Functions
- Partner with security teams to resolve data governance and security findings (PII exposure, access controls)
Collaboration
- Partner with brand stakeholders and third-party integration partners, enforcing access and environment guardrails
- Work closely with data analysts, data scientists, and business teams to translate business needs into scalable data solutions
- Mentor engineers on data engineering, dbt/SQL, and AI-assisted development practices
Qualifications & Experience
- 3+ years of experience in Sr data engineering experience.
- 3+ years of experience in data engineering
- Strong expertise in SQL, Python, dbt, and Airflow/Cloud Composer.
- 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 mentor data engineers and influence technical strategy
Educational Qualifications
- Bachelor's degree in Computer Science, Mathematics, or Software Engineering
- Master's degree (preferred, not required)
- Relevant certifications a plus
Annual Salary Range: $130,000-$160,000/year, with a generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match.
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