Experian
data and technology
Sr.StaffEngineer(Python,Pyspark,AWS)
Neural analysis suggests this role is
optimal for not-applicable candidates.
“Sr. Staff Engineer (Python, Pyspark, AWS) at Experian. Skills: Python, Pyspark, AWS, cloud-native applications, microservices, Generative AI, LLMs, distributed data processing, Terraform. Lead the architecture and development of cloud-native applications, services, and platforms using Python and AWS. Build and manage cloud-native microservices leveraging AWS services”
Industry & Context.
translate business problems into scalable technical solutions
What They're Looking For.
Must Have
11+ years of software engineering experience, significant experience designing and delivering enterprise-scale systems, deep experience with AWS, including services such as Lambda, ECS/EKS, API Gateway, S3, IAM, EMR, CloudWatch, Step Functions, EventBridge, RDS/DynamoDB, Bedrock, Glue, or equivalent cloud-native services, Build application in React, TypeScript, and modern JavaScript (ES6+), Practical experience with Generative AI concepts and implementation patterns, including LLM integration, prompt engineering, embeddings, vector databases, RAG, AI safety, and model evaluation, hands-on expertise in Python, including API development, backend services, automation, testing, packaging, and production-grade code quality, working knowledge of Jupyter notebooks for experimentation, prototyping, and analytical development
What You'll Do.
Lead the architecture and development of cloud-native applications
and platforms using Python and AWS
Build and manage cloud-native microservices leveraging AWS services
Provide technical leadership across engineering teams
and platform teams to translate business problems into scalable technical solutions
Develop reusable frameworks
and automation patterns that accelerate engineering delivery
Drive adoption of engineering best practices including CI/CD
infrastructure as code
Build and optimize large-scale distributed data processing solutions using Apache Spark
and cloud data services
Evaluate emerging AI engineering tools
and agentic development platforms
recommending practical adoption paths
lightweight Docker images for Python
and GenAI applications
Build and maintain Infrastructure as Code using Terraform for AWS cloud resources and platform components
How You'll Work.
Team & Collaboration
Partner with product, security, architecture, data science, and platform teams; Provide technical leadership across engineering teams
Full Job Description
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. * Lead the architecture and development of cloud-native applications, services, and platforms using Python and AWS. * Build and manage cloud-native microservices leveraging AWS services such as Lambda, ECS, S3,Glue,RDS/DynamoDB, EMR, glue and EKS . * Provide technical leadership across engineering teams, driving design reviews, architecture decisions, coding standards, and operational excellence. * Partner with product, security, architecture, data science, and platform teams to translate business problems into scalable technical solutions. * Develop reusable frameworks, libraries, APIs, and automation patterns that accelerate engineering delivery. * Drive adoption of engineering best practices including CI/CD, infrastructure as code, test automation, observability, secure SDLC. * Build and optimize large-scale distributed data processing solutions using Apache Spark, PySpark, SQL, and cloud data services. * Evaluate emerging AI engineering tools, LLM frameworks, model providers, and agentic development platforms, recommending practical adoption paths. * Design, build, and maintain secure, lightwe
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