Data Architect

Were seeking a highly experienced Principal Data Engineer to drive the architecture strategy and delivery of data pipelines across our Enterprise Data platform. This role combines hands-on engineering technical leadership and data governance strategy.

Youre passionate about building reliable scalable data pipelines with Python Airflow and dbt Coreand about setting the standards that govern our data across its full life cycle. Youll partner closely with Product and Architecture leadership to set technical direction while mentoring engineers across the team.

Lead the architecture and strategy for ETL/ELT pipelines using Python Airflow and dbt Core across the Enterprise Data platform.

Define and drive data management standards across the full data life cycle ingestion transformation quality governance retention and archival.

Partner with Product Architecture and business stakeholders on data strategy and roadmap planning.

Mentor engineers across multiple experience levels and set engineering best practices for pipeline development.

Drive adoption of cloud-native GCP-based orchestration such as Cloud Composer and storage such as GCS.

Own data governance cataloging and lineage strategy.

Lead root-cause analysis and performance optimization for large-scale data pipelines.

Drive CI/CD automation and observability for data pipelines.

Required qualifications

8 years of experience in data engineering with leadership responsibility.

Deep expertise in PythonApache AirflowETL/ELT architecture at enterprise scaledbt Core

Deep understanding of data management principles and the full data life cycle.

Proven experience architecting large-scale data pipelines and data platforms. Strong SQL and data warehousing expertise.

Experience with cloud-native data platforms with a preference for Google Cloud Platform (GCP); other cloud platforms are also acceptable.

Experience mentoring engineers and leading technical initiatives.

Strong communication skills for partnering with stakeholders across the business.

Deep experience with GCP including Google Cloud Storage (GCS) and Cloud Composer.

Experience with Kafka or other event streaming platforms.

Experience with data governance and cataloging tools. Experience with CI/CD and observability tooling for data pipelines.