Google Cloud Platform Data Engineer (Lead or Architect)

Job Description

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**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 -**
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**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:
– BigQuery
– Cloud SQL
– 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).