About the role
Responsibilities:
- Design, build, and maintain ETL/ELT pipelines from enterprise applications, internal services, and third-party APIs.
- Design, develop, and operationalize robust and scalable data pipelines from enterprise applications, internal services, and third-party APIs that support business needs.
- Lead in designing and building production data pipelines from data ingestion to consumption using GCP services, Python, BigQuery, DBT, SQL, Apache Airflow, Celigo, etc.
- Drive AI adoption across the team's engineering workflows; the team has a mandate for AI adoption, and you'll be expected to be a role model, champion, remove friction, and help engineers integrate AI tools into their daily development, code review, documentation, and debugging practices.
- Design [EC5] and oversee data models in a medallion architecture.
- Mandate high standards for data validation, profiling, reconciliation, and quality initiatives.
- Stay updated with industry trends and technologies to continuously improve our data engineering practices.
- This reads to me more like an IC; also, ETL/ELT reads as data integrations; it's more data engineering. I think Mark is a better person to describe data integrations.