Google Cloud Platform Data Engineer (Lead or Architect)

H1b Workable

Near by Relocation only 

Role - Lead Google Cloud Platform Data Engineer/ Architect 

Location - Palm Beach , FL (Hybrid, 3-4 days/ week)

Contract

Implementation partner - ********

End client  - Confidential 

Mode of interview - Video /  Virtual 

Exp - Lead  10+ years     -    15 years

          Architect 12+ years   -    15 years

Job Description:

We are looking for a highly experienced Lead Data Engineer/ Architect with deep expertise in Google Cloud Platform (Google Cloud Platform) to lead the design, development, and optimization of large-scale, cloud-native data platforms. The role requires strong hands-on capabilities along with technical leadership, architectural decision-making, and mentoring responsibilities.

Key Responsibilities

· Lead end-to-end design and implementation of scalable data architectures on Google Cloud Platform.

· Architect, develop, and optimize data pipelines and data storage solutions using Dataflow, Cloud SQL, and BigQuery.

· Own and optimize complex SQL queries and Python-based data processing frameworks replicating data from ERP systems.

· Establish best practices for data modeling, ETL/ELT frameworks, and pipeline orchestration.

· Drive DevOps and CI/CD strategies for data platforms using Google Cloud Platform-native tools.

· Ensure platform reliability, data quality, security, and cost optimization.

· Act as a technical advisor to stakeholders, translating business requirements into scalable data solutions.

· Mentor and guide junior and mid-level data engineers.

· Conduct design reviews, performance tuning, and production issue resolution.

Required Skills & Qualifications:

· 10–15 years of overall experience in data engineering and analytics platforms.

· Strong hands-on expertise in SQL and Python.

· Extensive experience with Google Cloud Platform, including:

o BigQuery

o Cloud SQL

o Dataflow (Apache Beam)

· Proven experience in Google Cloud Platform DevOps, including CI/CD pipelines, monitoring, logging, and automation.

· Strong understanding of distributed systems, data warehousing, and large-scale data processing.

· Experience designing and operating high-volume, high-availability data platforms.

· Hands-on experience with version control systems (Git).

Good to Have

· Experience with real-time/streaming architecture replicating data from legacy ERP systems.

· Knowledge of data governance, metadata management, and security best practices.

· Google Cloud Platform certifications (Professional Data Engineer / Cloud Architect).

· Experience working in large enterprise environments (Supply Chain knowledge a plus).