AWS DevOps

Skill: AWS Devops

Experience: 6 to 9 years

Location: AIA Chennai

Job Summary

This hybrid role seeks an Architect with nine to thirteen years of experience specializing in AWS and Python to design scalable data platforms for a multinational organization. The Architect will define solution blueprints ensure performance and security of cloud data workloads and collaborate with cross functional teams to deliver resilient analytics capabilities that support critical business decisions and societal impact through responsible data use.

Responsibilities

• Design robust cloud data architectures using AWS EMR and Python that enable scalable processing of large data volumes and support high value analytics workloads for business stakeholders
• Develop end to end data processing pipelines in AWS EMR using Python that transform raw data into trusted datasets and improve decision making for internal and external partners
• Optimize cluster configuration resource allocation and job orchestration on AWS EMR to enhance performance reliability and cost efficiency for data intensive applications
• Implement secure data access patterns encryption strategies and identity controls across AWS services so that company and customer data remains protected and compliant with internal policies
• Collaborate closely with data engineers data scientists and product teams to translate analytical requirements into practical cloud solutions that are maintainable and future ready
• Create detailed technical designs migration plans and integration patterns that guide teams in modernizing legacy data platforms into cloud native solutions on AWS
• Establish coding standards reusable frameworks and automation practices for Python based data processing that reduce defects improve reusability and accelerate delivery cycles
• Review solution implementations for alignment with architectural blueprints and provide clear technical guidance so that teams can correct deviations early and avoid rework
• Introduce observability practices such as logging metrics and alerting across AWS EMR and related services to ensure rapid detection of incidents and proactive capacity planning
• Partner with security and compliance colleagues to assess risks design mitigating controls and document architectures that support audits and regulatory commitments
• Guide optimization of data storage models partitioning strategies and compression choices so that platforms deliver strong query performance and reduced cloud spend
• Document architecture decisions data flow diagrams and operational runbooks that make solutions understandable maintainable and easier to onboard for new team members
• Contribute to innovation initiatives by evaluating emerging AWS capabilities and Python libraries and proposing improvements that enhance sustainability efficiency and social impact of data solutions
  
  

• Possess nine to thirteen years of experience working in architecture or senior engineering roles with a strong focus on designing data platforms and distributed processing solutions
• Demonstrate expert level proficiency in AWS EMR including setup tuning job scheduling and integration with services such as S3 Glue and data catalog solutions
• Show strong experience in Python for data engineering including development of modular pipelines error handling testing patterns and use of common data processing libraries
• Exhibit practical knowledge of cloud networking security concepts and identity controls on AWS to design architectures that protect sensitive data and enforce least privilege access
• Bring experience in designing or supporting hybrid work environments and collaborating across time zones using remote friendly practices to keep teams aligned and productive
• Display familiarity with modern data architectures such as data lakes and curated data layers with a focus on building reusable assets that can be shared across business domains
• Apply sound understanding of software engineering fundamentals version control and continuous integration practices to ensure that data solutions remain robust and traceable
• Communicate complex technical concepts clearly to non technical partners and document solutions in a structured manner that supports training and long term maintainability
• Value inclusive collaboration continuous learning and ethical data use so that the solutions created advance both business goals and positive outcomes for society