AWS Cloud Data Engineer

Summary

The AWS Data Engineer will be responsible for designing, implementing, and maintaining data solutions on Amazon Web Services (AWS) to support the organization's data and analytics needs. This role will focus on building scalable, secure, and efficient data pipelines, integrating data across systems, and leveraging AWS services to optimize data storage, processing, and retrieval. The AWS Data Engineer will collaborate with cross-functional teams to deliver robust and reliable data infrastructure

Essential Duties and Responsibilities:

• Serve as a shared resource across product teams to provide expertise and scalable solutions for data integration, modeling, and analytics across all products
• Design and implement scalable data pipelines using AWS services such as AWS Glue, AWS Data Pipeline, and Amazon Kinesis
• Create and maintain all Infrastructure-as-Code (IaC) for primary product teams using tools like AWS CloudFormation or CDK
• Develop and maintain data storage solutions using Amazon S3, Redshift, RDS, DynamoDB, or other AWS-managed databases
• Design and develop code pipelines for our primary product application to:
• Build application components
• Run automated tests created by the QA team
• Execute static code analysis
• Allow or prevent commits or PR merges based on predefined quality thresholds
  
• Deploy and manage AWS infrastructure resources as needed to support organizational and product-specific goals
• Implement monitoring, logging, and centralization of application instrumentation for real-time insights and troubleshooting
• Optimize ETL workflows to efficiently manage data across diverse sources and destinations
• Set up and manage AWS IAM policies, roles, and security-related configurations to ensure secure access and data protection
• Stay updated on AWS innovations and recommend tools or best practices to enhance the organization’s data ecosystem
• Create comprehensive documentation and provide training for AWS-based data solutions, ensuring knowledge transfer and ease of use
• Ensure all data processes and systems adhere to security best practices, aligning with OWASP Top 10, CWE Top 25 guidelines, and CIS AWS Foundations Benchmark
  
  
  

Further Expectations of the Role:

• Disciplined in approach to work product completion and timelines
• Must have analytical thought processes to make independent decisions
• Ability and willingness to work extended hours on a sporadic basis as required
• Ability and willingness to work on multiple assignments/projects in a fast-paced environment and meet tight deadlines
• Ability and willingness to work independently
• Ability to effectively formulate and communicate problems and ideas
• Demonstrate and provide outstanding customer and employee relations at all times
  
  
  

Qualifications:

• Minimum 5 years of applicable work experience. This level of knowledge is normally acquired through completion of a Bachelor’s Degree in a data-centric field (Computer Science, Economics, Information Systems, Data Analytics, etc.) and 3 years’ experience with demonstrated track record of successful technical leadership in the execution of large-scale data projects or equivalent combination of education and experience
• Strong analytical skills and the ability to translate data into actionable insights
• Excellent technical writing and oral communication skills
• Experience collaborating cross-functionally with internal and external stakeholders
• Travel Expectations: 0%
• Ability to pass stringent background investigations, required
• Clean driving record, required
  
  
  

Certified Banana Picker

About CCT

CCT is the creator of Casino Insight™, the award-winning platform trusted by more than 350 casinos worldwide to automate cage operations, revenue audits, and operational analysis. Since 2012, Casino Insight has helped casinos replace manual work with streamlined workflows, improving accuracy, compliance, and profitability.

Headquartered in Tulsa, Oklahoma, CCT integrates seamlessly with leading casino management, hospitality, and financial systems—delivering measurable ROI and empowering teams to work smarter at every level.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.