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Mid-level seniority, metro location, and broad GCP/data stack requirements create moderate applicant competition.
Core data engineering skills are transferable across industries, though GCP-specific and managerial experience raise domain bias.
Explicit 10+ years requirement plus mandatory GCP/dbt/BigQuery and people-management raises filtering strictness.
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Lead and manage a team of 6-12 data engineers working within the Google Cloud Platform ecosystem focusing on scalable Medallion Architecture data pipelines.
Design, build, and optimize ELT/ETL pipelines using dbt, BigQuery, Python, and oversee migration of legacy pipelines to GCP.
Drive Agile delivery processes and act as a technical liaison among business, product, and executive stakeholders to deliver enterprise data initiatives.
Minimum 10+ years of professional experience in data engineering or related roles.
At least 3 years of direct people management or technical lead experience.
Strong proficiency in GCP technologies including BigQuery, Cloud Storage, GKE, Pub/Sub, and Python with dbt and orchestration tools like Airflow.
Experience implementing Medallion Architecture and managing data governance, security, and operational performance in a cloud environment.
Experienced leader capable of balancing hands-on technical design and team management in a cloud-native GCP data engineering environment.
Proven track record delivering complex, scalable data warehouse solutions and migrating legacy ETL pipelines to cloud platforms.
Skilled in Agile methodologies with ability to manage cross-functional stakeholder expectations and translate business needs into technical roadmaps.