Description

Define technology vision and lead end-to-end architecture for Data Engineering, Data Warehousing, and AI/ML solutions on GCP.

This role is on-site.

Responsibilities

• Define short- and long-term technology vision, evaluating current landscapes and charting strategic paths forward.
• Design scalable, secure solutions using GCP-native services including BigQuery, Dataflow, Cloud Composer, Vertex AI, Dataproc, and Cloud Storage.
• Lead delivery on large-scale programs, owning timelines, quality, risk, and client satisfaction end-to-end.
• Build foundational architectures for microservices, event-driven systems, and online ML systems.
• Mentor delivery teams on engineering practices and bridge the gap between architecture decisions and execution realities.

Required Skills

• 12+ years in Data Engineering and Cloud-native technologies with deep GCP expertise.
• Hands-on mastery of BigQuery, Dataflow, Cloud Composer, Vertex AI, Dataproc, and GCP serverless infrastructure.
• Proven delivery of end-to-end Data Engineering, Data Warehousing, or Analytics platforms at scale.
• Strong programming skills in Python and/or Java.
• Experience with Agile, CI/CD, DevOps, and MLOps pipelines.
• Track record leading large, complex, client-facing delivery programs.
• Ability to manage cross-functional, cross-geography teams with clarity and accountability.
• Proficiency in SQL or similar structured querying languages (e.g., PLX, Dremel/Spanner).

Preferred Skills

• Google Cloud Professional Cloud Architect Certification.
• AWS experience, especially in hybrid cloud contexts.
• Docker & Kubernetes experience.

Key Skills

Education

Bachelor's degree