Google Cloud Platform Data Engineer

Overview

Hybrid
$50+
Accepts corp to corp applications
Contract - W2

Skills

Google Cloud Platform
BigQuery
Dataflow (Apache Beam)
Pub/Sub
Dataproc
Data Fusion
Composer Solid understanding of SQL
Python
data orchestration
IAM
CI/CD pipelines
data governance
security
Best practices
Terraform
Cloud Build
Jenkins
DataOps Practices
Apache Spark
Kafka
Data modeling
ETL frameworks
Data architecture design
streaming
batch data processing
Cloud Storage
networking concepts
GCP
Version control (Git)

Job Details

*Experience: 10-12 years

Job Summary:

We are seeking a skilled Google Cloud Platform Data Engineer to design, build, and optimize data pipelines and architectures on Google Cloud Platform. The ideal candidate will have strong expertise in data integration, transformation, and analytics using Google Cloud Platform s native services, with a focus on scalability, reliability, and performance.

Key Responsibilities:

Design, develop, and maintain ETL/ELT pipelines using Google Cloud Platform tools such as Dataflow, Dataproc, Composer, and BigQuery.

Implement data ingestion frameworks from multiple sources (structured/unstructured, batch/streaming) using Pub/Sub, Cloud Storage, and Cloud Functions.

Build and manage data models, data marts, and data warehouses in BigQuery.

Optimize query performance, partitioning, and clustering strategies in BigQuery.

Collaborate with data scientists, analysts, and business stakeholders to provide clean, reliable data sets.

Manage and automate workflows using Cloud Composer (Airflow).

Ensure data quality, security, and compliance through governance policies and IAM controls.

Monitor, troubleshoot, and optimize data processes for efficiency and cost-effectiveness.

Participate in CI/CD processes for data pipelines using Cloud Build, Terraform, or similar tools.

Required Skills & Experience:

Strong experience with Google Cloud Platform data services:

BigQuery, Dataflow (Apache Beam), Pub/Sub, Dataproc, Data Fusion, Composer

Solid understanding of SQL, Python, and data modeling.

Experience with ETL frameworks, data orchestration, and data architecture design.

Hands-on experience with streaming and batch data processing.

Knowledge of Cloud Storage, IAM, and networking concepts in Google Cloud Platform.

Familiarity with version control (Git) and CI/CD pipelines.

Understanding of data governance, security, and best practices.

Preferred Qualifications:

Google Professional Data Engineer Certification.

Experience with Terraform, Cloud Build, Jenkins, or other automation tools.

Exposure to machine learning pipelines or DataOps practices.

Familiarity with Apache Spark, Kafka, or similar data technologies.

Soft Skills:

Excellent problem-solving and analytical skills.

Strong communication and collaboration skills across teams.

Ability to work in a fast-paced, agile environment.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.