Data Engineer II

Build robust solutions for transferring data from first and third-party applications to and from our data warehouse
Passionate about data quality and availability, driving to resolution through high collaboration with team members.
Making decisions as a team. The things you build will be maintained and improved upon by others; there is a shared responsibility to make defensible design considerations.
Develop hardened and repeatable (CI/CD) data models and pipelines to enable reporting, modeling, and machine learning.
Improve data availability to our enterprise clients through a mix of traditional push delivery, cloud, and event-driven (eg: API, grpc) data sharing methods.
Ensure data quality through automated monitoring and alerting, and occasionally serving within an on-call rotation.
Leverage Google Cloud (GCP) tools (eg: Cloud Run, Cloud Function, Vertex AI, App Engine, Cloud Storage, IAM, etc.) and services (eg: Astronomer - Apache Airflow) to bring data workloads to production.
Collaborate with product, engineering, stakeholders and data teams to deliver informed solutions to platform and client needs.

Build robust solutions for transferring data from first and third-party applications to and from our data warehouse
Passionate about data quality and availability, driving to resolution through high collaboration with team members.
Making decisions as a team. The things you build will be maintained and improved upon by others; there is a shared responsibility to make defensible design considerations.
Develop hardened and repeatable (CI/CD) data models and pipelines to enable reporting, modeling, and machine learning.
Improve data availability to our enterprise clients through a mix of traditional push delivery, cloud, and event-driven (eg: API, grpc) data sharing methods.
Ensure data quality through automated monitoring and alerting, and occasionally serving within an on-call rotation.
Leverage Google Cloud (GCP) tools (eg: Cloud Run, Cloud Function, Vertex AI, App Engine, Cloud Storage, IAM, etc.) and services (eg: Astronomer - Apache Airflow) to bring data workloads to production.
Collaborate with product, engineering, stakeholders and data teams to deliver informed solutions to platform and client needs.

4+ years working in a data engineering role that supports incoming/outgoing feeds as well as analytics and data science teams
2+ years of Python or similar experience writing efficient, testable, and readable code
Deep SQL experience with columnar databases such as Google BigQuery, Snowflake, or Amazon Redshift
Comfortable designing an end-to-end data pipeline in cloud frameworks (such as GCP, AWS, Azure) with requirements from multiple stakeholders
Experience building CICD pipelines for data processing using tools such as Docker, CircleCI, dbt, git, etc
Able to manage infrastructure using IAC tools such as Terraform or Pulumi
Experience with common data orchestration tools such as Apache Airflow (or similar) to manage SLOs and processing dependencies
Experience in building streaming / real-time ingestion pipelines
Experience with creating alerts and monitoring pipelines which contribute to overall data governance.
Experience with containerization and container orchestration technologies with cloud architecture and implementation features (single- and multi-tenancy, orchestration, elastic scalability)
Familiarity with standard IT security practices such as identity and access management (IAM), data protection, encryption, certificate, and key management.
Adaptability to learn new technologies and products as the job demands.