HonorVet Technologies
Python Engineer
Job Title: Python Engineer Duration: 12+ Months (W2 Only) Location: Costa Mesa, CA or Allen, TX (1 day/week) Job Description: The client is seeking a Senior Staff Architect to join our FSD Product Development team. This is a great opportunity for someone who specializes in building large-scale, cloud-based big data and MLOps platforms and APIs to access timely, accurate, and relevant data. An ideal candidate will have built scalable platforms that can easily accommodate and integrate different data sources and provide comprehensive data capabilities to all Experian products and delivery channels. Responsibilities What you'll be doing: Partner with Architecture/Product/CloudOps/Engineering teams to craft highly scalable, flexible, and resilient cloud architectures that address customer business problems and accelerate the adoption of cloud services. Design and implement complex architectural solutions using AWS design principles, best practices, and industry standards. Build scalable, reliable, and cost-efficient ML pipelines using Python, AWS services (SageMaker, Lambda, Step Functions, S3, ECR, etc.), and container technologies (Docker, ECS/Fargate). Lead technical design reviews, guide engineering teams on architectural best practices, and create high-level and low-level design documents. Determine code quality and test coverage, design and implement tests to ensure software is built to the highest quality possible. Communicate and explain technical/architectural decisions to product, development, and delivery teams. Drive continual improvement in quality and efficiency, including defect prevention/root cause analysis, as well as suggest and adopt improvements to technology and efficiency. Perform proof of concept work for integrating new technologies into the existing product. Comprehend detailed project specifications and adapt to various technologies while simultaneously working on multiple projects. Participate in reviews of software engineers' code to deliver high-quality solutions. Work closely with the product and actively participate in business requirement analysis. Lead and mentor junior members of the team. Research and implement performance tuning and enhancements to existing and newly developed systems to maximize performance from the existing infrastructure. Knowledge, Experience & Qualifications What your background looks like: Education:
BS in Computer Science or related fields; MS preferred. Experience:
8+ years' experience in key engineering roles (technical lead, software engineer, software architect). 5+ years' experience using Amazon Web Services (AWS) to architect and deploy reliable, cost-effective, scalable, and secure cloud-native solutions. Experience working in an agile/scrum environment.
Technical Skills:
Deep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework, industry standards, and best practices. Strong experience with MLOps platforms such as AWS SageMaker, Kubeflow, or MLflow. Hands-on design and development experience using Python, Flask, Django, AsyncIO, etc. Good understanding of distributed software applications, including system integration, testing, and troubleshooting. Experience monitoring the health of distributed systems and strategies for error detection and recovery. Systems integration experience, including design and development of APIs, Real-Time Systems, and Microservices. Current cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate, etc.). Passionate about learning new frameworks, building new processes and procedures from scratch, and training analysts on best practices. Familiarity with CI/CD processes, testing frameworks, and practices (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness, etc.). Experience integrating with async messaging, logging, or queues, such as Kafka, RabbitMQ, or SQS. Strong knowledge of software development processes and project management methodologies. Strong problem-solving and analytical skills. Excellent communication and documentation skills with the ability to lead cross-functional initiatives. Enjoy working in a dynamic, fast-moving, and challenging environment. Good team player and experience working with globally distributed teams.
Required Skills: Amazon Web Services (AWS) Deep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework Strong experience with MLOps platforms such as AWS SageMaker, Kubeflow, or MLflow Development experience using Python, Flask, Django, AsyncIO, etc. Experience in monitoring the health of distributed systems and a strategy for error detection and recovery Systems integration experience, including design and development of APIs, Real-Time Systems, and Microservices Current cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate, etc.) Demonstrable familiarity with CI/CD process, testing frameworks, and practices (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness, etc.) Experience integrating with async messaging, logging, or queues, such as Kafka, RabbitMQ, or SQS Additional Skills: Experience with monitoring and logging tools
Dynatrace, Splunk, etc. Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn Experience with Kubeflow, MLflow, Airflow, or similar workflow orchestration tools Building automated and scheduled pipelines for analytical processes Nice to Have: Experience with monitoring and logging tools
Dynatrace, Splunk, etc. Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn Experience with Kubeflow, MLflow, Airflow, or similar workflow orchestration tools Building automated and scheduled pipelines for analytical processes
Job Title: Python Engineer Duration: 12+ Months (W2 Only) Location: Costa Mesa, CA or Allen, TX (1 day/week) Job Description: The client is seeking a Senior Staff Architect to join our FSD Product Development team. This is a great opportunity for someone who specializes in building large-scale, cloud-based big data and MLOps platforms and APIs to access timely, accurate, and relevant data. An ideal candidate will have built scalable platforms that can easily accommodate and integrate different data sources and provide comprehensive data capabilities to all Experian products and delivery channels. Responsibilities What you'll be doing: Partner with Architecture/Product/CloudOps/Engineering teams to craft highly scalable, flexible, and resilient cloud architectures that address customer business problems and accelerate the adoption of cloud services. Design and implement complex architectural solutions using AWS design principles, best practices, and industry standards. Build scalable, reliable, and cost-efficient ML pipelines using Python, AWS services (SageMaker, Lambda, Step Functions, S3, ECR, etc.), and container technologies (Docker, ECS/Fargate). Lead technical design reviews, guide engineering teams on architectural best practices, and create high-level and low-level design documents. Determine code quality and test coverage, design and implement tests to ensure software is built to the highest quality possible. Communicate and explain technical/architectural decisions to product, development, and delivery teams. Drive continual improvement in quality and efficiency, including defect prevention/root cause analysis, as well as suggest and adopt improvements to technology and efficiency. Perform proof of concept work for integrating new technologies into the existing product. Comprehend detailed project specifications and adapt to various technologies while simultaneously working on multiple projects. Participate in reviews of software engineers' code to deliver high-quality solutions. Work closely with the product and actively participate in business requirement analysis. Lead and mentor junior members of the team. Research and implement performance tuning and enhancements to existing and newly developed systems to maximize performance from the existing infrastructure. Knowledge, Experience & Qualifications What your background looks like: Education:
BS in Computer Science or related fields; MS preferred. Experience:
8+ years' experience in key engineering roles (technical lead, software engineer, software architect). 5+ years' experience using Amazon Web Services (AWS) to architect and deploy reliable, cost-effective, scalable, and secure cloud-native solutions. Experience working in an agile/scrum environment.
Technical Skills:
Deep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework, industry standards, and best practices. Strong experience with MLOps platforms such as AWS SageMaker, Kubeflow, or MLflow. Hands-on design and development experience using Python, Flask, Django, AsyncIO, etc. Good understanding of distributed software applications, including system integration, testing, and troubleshooting. Experience monitoring the health of distributed systems and strategies for error detection and recovery. Systems integration experience, including design and development of APIs, Real-Time Systems, and Microservices. Current cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate, etc.). Passionate about learning new frameworks, building new processes and procedures from scratch, and training analysts on best practices. Familiarity with CI/CD processes, testing frameworks, and practices (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness, etc.). Experience integrating with async messaging, logging, or queues, such as Kafka, RabbitMQ, or SQS. Strong knowledge of software development processes and project management methodologies. Strong problem-solving and analytical skills. Excellent communication and documentation skills with the ability to lead cross-functional initiatives. Enjoy working in a dynamic, fast-moving, and challenging environment. Good team player and experience working with globally distributed teams.
Required Skills: Amazon Web Services (AWS) Deep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework Strong experience with MLOps platforms such as AWS SageMaker, Kubeflow, or MLflow Development experience using Python, Flask, Django, AsyncIO, etc. Experience in monitoring the health of distributed systems and a strategy for error detection and recovery Systems integration experience, including design and development of APIs, Real-Time Systems, and Microservices Current cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate, etc.) Demonstrable familiarity with CI/CD process, testing frameworks, and practices (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness, etc.) Experience integrating with async messaging, logging, or queues, such as Kafka, RabbitMQ, or SQS Additional Skills: Experience with monitoring and logging tools
Dynatrace, Splunk, etc. Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn Experience with Kubeflow, MLflow, Airflow, or similar workflow orchestration tools Building automated and scheduled pipelines for analytical processes Nice to Have: Experience with monitoring and logging tools
Dynatrace, Splunk, etc. Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn Experience with Kubeflow, MLflow, Airflow, or similar workflow orchestration tools Building automated and scheduled pipelines for analytical processes