Location: Charlotte, NC
Salary: $69.00 USD Hourly - $74.00 USD Hourly
Description: Senior Software Engineer - Data Engineering (Google Cloud Platform & AI)Location: Charlotte, NC (Preferred)
- 300 S Brevard St, Charlotte, NC
- 1525 W T Harris Blvd, Charlotte, NC
Work Model: Hybrid (3 days onsite)
Employment Type: Contract (12 months, with expected extension)
About the RoleWe are looking for a Senior Software Engineer specializing in Data Engineering to design and build scalable data platforms and AI-powered solutions on Google Cloud Platform (Google Cloud Platform). In this role, you will partner with cross-functional teams to develop modern data architectures, production-grade pipelines, and integrated machine learning capabilities that drive business impact.
This position supports critical initiatives including cloud migration, data platform modernization, and AI enablement through 2026 and beyond.
What You'll Do- Design and build scalable data pipelines (ETL/ELT) on Google Cloud Platform
- Develop and optimize data warehouses and data lakes using BigQuery and related services
- Implement data orchestration, transformation, and quality frameworks using tools like Cloud Composer, dbt, or Dataform
- Deploy and integrate machine learning models using Vertex AI and other Google Cloud Platform AI services
- Collaborate with data scientists, analysts, and engineering teams to deliver end-to-end data solutions
- Improve performance, scalability, reliability, and cost efficiency of data systems
- Monitor, troubleshoot, and enhance pipeline and platform performance
Minimum Qualifications- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 7+ years of software engineering experience, with a focus on data engineering
- Hands-on experience building solutions on Google Cloud Platform (Google Cloud Platform)
- Strong experience with:
- BigQuery (data warehousing and analytics)
- Data processing tools (Dataflow, Dataproc, or Data Fusion)
- Workflow orchestration (Cloud Composer / Airflow)
- Cloud Storage and Pub/Sub
- Proficiency in Python and SQL
- Solid understanding of data modeling and warehousing concepts (e.g., star and snowflake schemas)
- Experience deploying and integrating AI/ML models in production environments
Preferred Qualifications- Experience with Vertex AI for ML model deployment and lifecycle management
- Familiarity with dbt, Dataform, or similar tools for data transformation
- Knowledge of MLOps practices, model monitoring, or LLM/RAG applications
- Experience with containerization and orchestration (Docker, Kubernetes/GKE)
- Experience building real-time data pipelines using Pub/Sub and Dataflow
- Google Cloud Professional Data Engineer or ML Engineer certification
Additional Information- Candidates must submit resumes through Beeline to be considered
- Please do not alter resumes to match job descriptions; skills should reflect actual experience
- Direct candidate solicitation or contact with the hiring manager is not permitted
Impact You'll HaveYou'll play a key role in delivering a high-visibility data platform roadmap, including large-scale Google Cloud Platform migrations, advanced analytics capabilities, and AI-powered solutions that support critical business outcomes.
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