Google Cloud Platform Data Engineer

We are seeking a highly skilled Senior Google Cloud Platform Data Engineer to design, build, and optimize scalable, cloud-native data pipelines and platforms on Google Cloud Platform (Google Cloud Platform). This role will act as the primary technical owner for implementing data pipelines aligned with Enterprise Architecture (EA) standards and driving engineering best practices across the data ecosystem.

You will collaborate closely with cross-functional teams including Enterprise Architecture, Platform Engineering, Data Activation, and Solution Architects to enable robust data ingestion (batch and streaming) and transformation pipelines across multiple data sources.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines on Google Cloud Platform for batch and real-time processing.
• Implement data ingestion frameworks (push/pull) using services like Dataflow, DataStream, Pub/Sub, and Cloud Run.
• Build and optimize data transformation pipelines using BigQuery, Dataform, and Spark-based frameworks.
• Act as the technical lead/owner ensuring alignment with EA-approved data architecture.
• Drive best practices in data engineering, including CI/CD, testing, monitoring, and cost optimization.
• Collaborate with cross-functional teams to deliver end-to-end data solutions.
• Ensure data quality, reliability, governance, and performance across pipelines.

Technical Qualifications

Experience

• 6+ years of experience in data engineering, with strong focus on Google Cloud Platform (Google Cloud Platform).
• Google Cloud Platform Professional Data Engineer certification - must have

Core Google Cloud Platform Expertise

Strong hands-on experience with:

• Medallion architecture (Centralized Hub/Spoke model)
• BigQuery (data warehousing & optimization)
• Dataform (SQL-based transformations)
• Dataflow (batch & streaming pipelines)
• Datastream (CDC ingestion)
• Cloud Composer (Airflow) (orchestration)
• Dataproc (Spark/PySpark)
• Cloud Run
• Cloud Storage
• Pub/Sub

Programming & Querying

Advanced proficiency in:

• Python
• PySpark / Apache Spark
• SQL (complex transformations, performance tuning)

Data Architecture

Deep understanding of:

• Data modeling techniques
• Medallion architecture (Bronze/Silver/Gold layers)
• Centralized Hub/Spoke data platform design

Preferred Skills

• Experience with real-time streaming architectures
• Familiarity with CI/CD pipelines (Terraform, Cloud Build, GitOps)
• Strong understanding of data governance, security, and compliance
• Experience working in large enterprise or utility/regulated environments

Soft Skills

• Strong ownership and accountability
• Ability to work across distributed teams and vendors
• Excellent communication with technical and non-technical stakeholders