Data Engineer with Google Cloud Platform

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Role: Data Engineer with Google Cloud Platform

Location: Charlotte, NC (ONSITE)

Key Responsibilities

Architect and own scalable, secure, cloud-native data platforms on Google Cloud Platform Design, build, and optimize batch and real-time data pipelines using BigQuery, Dataflow, Pub/Sub, and Dataproc Lead BigQuery performance tuning and cost optimization (partitioning, clustering, query efficiency)

Orchestrate workflows using Cloud Composer (Apache Airflow)

Enable Al/ML and GenAl integration via Vertex Al and BigQuery ML

Enforce data governance, security, reliability, and FinOps best practices

Mentor engineers, conduct design/code reviews, and set enterprise data engineering standards

• Collaborate with product, analytics, and data science teams to deliver business-critical insights
  
  

Key Skill Sets

• Google Cloud Platform Data Services: BigQuery, Dataflow (Apache Beam), Pub/Sub, Cloud Storage, Cloud Composer, Dataproc
• Programming & SQL: Advanced SQL, Python (Java/Scala a plus)
• Data Engineering: ETL/ELT, streaming & batch processing, data modeling, distributed systems
• Modern Architectures: Lakehouse, Apache Iceberg, Data Mesh concepts
• Al/ML Enablement: Vertex Al, BigQuery ML, GenAl-ready pipelines DevOps & laC: Terraform, CI/CD, DataOps practices
  
  

Leadership: Architecture ownership, mentoring, stakeholder communication, problem solving

• Certification: Google Cloud Professional Data Engineer (strongly preferred / often mandatory)