We are seeking a seasoned Solutions Architect with 15-20 years of experience in designing and delivering enterprise-grade data and application solutions. The ideal candidate will have strong expertise across Data Engineering , Cloud platforms (AWS) , and full-stack development using Java (Spring Boot, Microservices) and Python (including PySpark) . This role demands a strategic mindset combined with hands-on capabilities to lead architectural efforts across cloud-native data and application ecosystems.
Key Responsibilities:
Design and implement end-to-end cloud-native solutions leveraging AWS, Java, and Python technologies.
Lead architecture and development of data pipelines using PySpark and AWS Glue , and backend systems using Java (Spring Boot) and Microservices .
Collaborate with stakeholders to understand business requirements and translate them into scalable, secure, and high-performance technical solutions.
Architect data lakes , data warehouses , and real-time streaming platforms on AWS using services like S3, Redshift, Glue, EMR, Lambda, Kinesis , etc.
Design and build microservices-based architectures using Java , Spring Boot , and containerization technologies (Docker, Kubernetes).
Drive best practices for CI/CD , DevOps, and infrastructure-as-code (Terraform, CloudFormation).
Lead design reviews, architecture evaluations, and performance tuning across systems.
Provide technical leadership, mentorship, and architectural governance to engineering teams.
Ensure solutions adhere to security, compliance, scalability, and cost-efficiency standards
Requirements Required Skills and Experience:
15-20 years of experience in enterprise software architecture, with deep expertise in data engineering , cloud solutions , and backend development .
Strong hands-on skills in Python , PySpark , and Java (Spring Boot, Microservices) .