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C
Cognizant
GCP Engineer
Career Insights for Cloud Architect
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What they do
A Cloud Architect designs a business' cloud computing strategy. Oversees application architecture and deployment in cloud environments. Integrates cloud applications with other applications. Acts as an advisor to the business on ongoing cloud management strategies.
$118,027 / year median in Texas
+14% projected growth
Job Description
Please note, this role is not able to offer visa transfer or sponsorship now or in the future. About the role As a GCP Engineer, you will make an impact by designing, building, and optimizing scalable data pipelines and infrastructure on Google Cloud Platform, with hands-on, production-grade experience across Cloud Run, Cloud Composer, BigQuery, and Python. You will play a key role in architecting robust data solutions that support analytics, reporting, and business intelligence across the organization. You will be a valued member of the Data Engineering team and work collaboratively with data scientists, analysts, and business stakeholders. In this role, you will:
- Design, develop, and maintain scalable ETL/ELT data pipelines on GCP, integrating services such as Pub/Sub, Cloud Storage, Dataflow, and Cloud Functions.
- Build and orchestrate complex workflows using Cloud Composer (Apache Airflow).
- Develop and deploy containerized microservices and event-driven data processing jobs using Cloud Run.
- Design efficient, high-performance data models and queries in BigQuery, including partitioning, clustering, and cost optimization strategies.
- Collaborate with data scientists, analysts, and business stakeholders to translate data requirements into technical solutions, while mentoring junior and mid-level engineers.
- 10+ years of overall experience in data engineering, software engineering, or related fields, including 5+ years of hands-on experience with Google Cloud Platform (GCP).
- Strong, demonstrable expertise in BigQuery, including query optimization, schema design, and partitioning/clustering.
- Hands-on experience with Cloud Composer / Apache Airflow (DAG design, orchestration, scheduling) and Cloud Run (containerized deployments, serverless architecture).
- Advanced proficiency in Python, including data processing libraries such as Pandas or PySpark, along with solid SQL and query performance tuning skills.
- Strong understanding of data warehousing concepts, data modeling (star/snowflake schema), and ETL/ELT design patterns. These will help you stand out
- Experience with additional GCP services such as Cloud Storage, Pub/Sub, Dataflow, Dataproc, or IAM.
- Familiarity with CI/CD pipelines and infrastructure-as-code tools such as Terraform, Cloud Build, or GitHub Actions.
- Experience with Git-based version control and Agile/Scrum development practices.