Senior Cloud Solution Engineer

Job Description: Senior Cloud Solution Engineer
Location: Charlotte, NC (Hybrid)


Overview: We are seeking a highly skilled Senior Cloud Solution Engineer with expertise in solution building, design, and optimization on cloud platforms. The ideal candidate will have experience with BigQuery, Jupyter Notebooks, Airflow, Dataplex/Dataproc, and advanced optimization and scheduling techniques to transform and manage data effectively.


Responsibilities:
• Solution Design and Architecture: Design scalable, robust, and secure cloud-based solutions leveraging tools like BigQuery, Dataplex, and Dataproc for data transformation and management.
• Data Transformation and Processing: Implement and optimize ETL/ELT pipelines using Dataproc, Dataplex, and other cloud-native tools.
• Scheduling and Workflow Automation: Develop, deploy, and manage workflows using Apache Airflow to ensure efficient scheduling and data orchestration.
• Data Analysis and Visualization: Utilize Jupyter Notebooks for exploratory data analysis, prototyping, and visualization to provide actionable insights.
• Performance Optimization: Design and implement optimization strategies for data processing pipelines to enhance performance and reduce costs.
• Collaboration: Work closely with cross-functional teams, including data engineers, analysts, and stakeholders, to gather requirements and deliver tailored solutions.
• Cloud Governance: Ensure compliance with best practices in cloud security, governance, and data integrity.
• Continuous Improvement: Stay updated with the latest advancements in cloud technologies and recommend tools and practices to enhance team efficiency and productivity.
Qualifications:
• Proven experience in solution building and design on cloud platforms (e.g., GCP, AWS, Azure).
• Strong hands-on expertise with BigQuery, Dataplex, Dataproc, and other cloud-native data tools.
• Proficiency in workflow management and scheduling tools such as Apache Airflow.
• Experience with Jupyter Notebooks for data analysis and visualization.
• Solid understanding of optimization techniques and scheduling algorithms for large-scale data processing.
• Programming skills in Python, SQL, and cloud SDKs.
• Familiarity with distributed computing, data lakes, and data warehouses.
• Strong problem-solving, analytical, and communication skills.
• Knowledge of cloud security and compliance standards.
Preferred Skills:
• Experience with ML/AI models integrated into data pipelines.
• Familiarity with other cloud services (e.g., AWS Redshift, Azure Synapse).
• Certification in cloud platforms such as Google Cloud Professional Data Engineer or similar.