Ramp Group is hiring one Data Engineer to perform the following duties:
• Explore hidden patterns in large datasets using Python, AWS services, and advanced analytics techniques.
• Develop machine learning models (e.g., regression, clustering, decision trees) with Python and AWS Glue for data preprocessing.
• Build scalable data ingestion systems and automated workflows to process large volumes of data using AWS services.
• Implement statistical and machine learning solutions to address business challenges using AWS.
• Create dynamic data visualizations and dashboards with Tableau and Power BI to drive actionable insights.
• Design and optimize ETL pipelines using Python, AWS (Glue, lambda, AWS Step Functions etc.) for efficient data processing.
• Manage and deploy serverless data architectures with AWS CDK and AWS SAM for cost-effective, scalable solutions.
• Maintain and optimize ETL scripts and jobs on AWS to support reporting, dashboards, models, and ad hoc analysis.
• Enhance AWS resource performance and reduce costs by utilizing Auto Scaling, right-sizing, cost management tools, etc.
• Clean and analyze data using statistical techniques, such as outlier detection, imputation, and transformation.
• Collaborate closely with client teams to understand requirements and effectively manage expectations.
• Work with cloud engineers to develop solutions for big data migration, storage, and processing on AWS.
• Use Git, GitHub, and GitLab for version control, code collaboration, and tracking changes.
Terms of Employment
• Wage: $45.87 – $48.08 per hour, 40 hours per week
• Competitive benefits package
• Permanent full-time
• Start immediately
• Location of work: 318-15225 104th Avenue, Surrey, British Columbia, V3R 6Y8
• Language of work: English
Requirements
• Bachelor’s degree in computer science, statistics, mathematics or another related discipline
• One year of experience working independently with minimal supervision or technical guidance as a data engineer with demonstrable familiarity with big data and machine learning models
• Must have strong programming skills
To apply, please email a CV or resume highlighting relevant experience and skills to [email protected].