Python Engineer

Senior Software Engineer - Python DeveloperExperian is seeking a Senior Staff Engineer (Senior Python Developer) to join our 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.ResponsibilitiesWhat you'll be doing:Partners 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.Designs and implements 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.Determines code quality and test coverage, designs and implements tests to make sure software is built to the highest quality possible.Communicate and explain technical/architectural decisions to product, development, and delivery teamsDrive 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.Ability to comprehend detailed project specifications, as well as the ability to adapt to various technologies and simultaneously work on multiple projects.Participates 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 gain the most performance from the existing Infrastructure.Knowledge, Experience & QualificationsWhat your background looks like:BS in Computer Science or related fields; MS preferred8+ years' experience in key engineering roles, such as technical lead, software engineer, and 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 environmentDeep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework, industry standards, and best practicesStrong 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 troubleshootingExperience in monitoring the health of distributed systems and a strategy for error detection and recoverySystems integration experience, including design and development of APIs, Real-Time Systems, and MicroservicesCurrent cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate...etc.)Passionate to learn new frameworks, building new processes and procedures from scratch, and training the analysts on best practices.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.Strong knowledge of software development process 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 environmentGood team player and work with globally distributed teams.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.