The Aspen Group (TAG) is looking to architect, build, and optimize scalable cloud-native data platforms to power business insights and decision-making
Requirements
- 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.
- Experience with streaming data pipelines (Kafka, Pub/Sub, Dataflow, etc.)
Responsibilities
- 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.
- 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.
- Work closely with data analysts, data scientists, and business teams to translate business needs into scalable data solutions.
Other
- Ability to lead teams, mentor engineers, and influence technical strategy.
- A generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match
- Onsite 4 days/week in Chicago office (Fulton Market District)
- Salary: $147,000 - 175,000/year
- Advocate for modern data engineering practices, including data observability and monitoring.
