GCP Cloud Engineer

Vaco is hiring a GCP Cloud Engineer for a direct hire opportunity in the greater Cincinnati area. This role requires candidates to be local to the Cincinnati area, as regular in office meetings are required. Only local candidates will be considered for this role. No C2C solicitations. Our client is in the midst of leading a migration of data from SQL Server to GCP. As their GCP Cloud Engineer, you will architect and build robust ingestion frameworks, establish scalable CI/CD and DataOps practices, and develop high-performance data pipelines using Python and Apache Spark. Key Responsibilities

Design, build, and optimize scalable data pipelines and ingestion frameworks on

Google Cloud Platform (GCP) . Migrate existing SQL Server-based data infrastructure to GCP services such as

BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer , and

Cloud Functions . Develop, deploy, and monitor robust CI/CD pipelines for data workflows using

Terraform, Cloud Build, or similar tools . Champion best practices in

DataOps

to automate, monitor, and validate data pipelines for reliability and performance. Collaborate with product, analytics, and engineering teams to ensure availability, reliability, and accuracy of data used in critical customer-facing solutions and internal operations. Work with structured and unstructured data sources and apply data transformation techniques using

Python, PySpark , and

SQL . Support and improve existing data infrastructure, monitor data quality and integrity, and troubleshoot data-related issues. Document architecture, processes, and pipelines clearly and comprehensively. Required Qualifications

5+ years

of hands-on experience in data engineering with a focus on cloud migration and modern cloud-native architecture. Deep expertise in

Google Cloud Platform (GCP) , particularly with:

BigQuery Cloud Storage Dataflow / Apache Beam Pub/Sub Cloud Composer (Airflow) Cloud Functions

Strong experience with

Python

and

Apache Spark / PySpark

for large-scale data processing. Proficiency in

SQL , especially with SQL Server and BigQuery dialects. Demonstrated experience building

CI/CD pipelines

for data workflows using tools such as

Cloud Build, GitHub Actions, Terraform, dbt , etc. Familiarity with

DataOps

practices and tools for orchestration, testing, and monitoring. Experience migrating and transforming legacy data sources (e.g., SQL Server) into cloud data warehouses. Strong understanding of data modeling, data quality, governance, and security best practices in the cloud. Preferred Qualifications

Experience with

real-time streaming data

using

Kafka or Pub/Sub . Familiarity with

dbt (data build tool)

and

Looker

or other BI tools. Experience working in a

SaaS or product-based

company with customer-facing analytics or features. Knowledge of infrastructure-as-code and containerization using

Docker/Kubernetes .

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