AWS Solution Architect – Data & Analytics (RARR Job 6403)

We are looking for an experienced AWS Solution Architect – Data & Analytics to design, architect, and deliver modern cloud-native data platforms on AWS. The ideal candidate will have strong expertise in AWS data services, large-scale analytics platforms, data engineering, and cloud architecture. You will work closely with business stakeholders, product teams, and engineering teams to build scalable, secure, and high-performance data solutions that support enterprise analytics and AI initiatives.

Key Responsibilities

Solution Architecture

• Design end-to-end data and analytics solutions on AWS.
• Define scalable, secure, and reusable architecture patterns for enterprise data platforms.
• Translate business requirements into technical architecture and implementation roadmaps.
• Prepare High-Level Design (HLD), Low-Level Design (LLD), and architecture documentation.
• Participate in architecture reviews and recommend best practices for cloud-native solutions.

AWS Data Platform

Design and implement solutions using AWS services including:

• Amazon S3
• AWS Glue
• AWS Lake Formation
• AWS Glue Data Catalog
• Amazon EMR (Apache Spark)
• Amazon Redshift
• Amazon Athena
• AWS Lambda
• AWS Step Functions
• Amazon Kinesis
• Amazon MSK (Kafka)
• AWS IAM
• AWS KMS
• Amazon CloudWatch

Data Engineering & Analytics

• Design Data Lake and Lakehouse architectures.
• Build scalable batch and real-time data processing pipelines.
• Develop ETL/ELT solutions using AWS-native services.
• Implement data ingestion, transformation, orchestration, and reporting solutions.
• Design dimensional, Data Vault, and domain-driven data models.
• Optimize data processing performance, scalability, and cost.

AI & Advanced Analytics

• Design AI-ready data platforms.
• Enable analytics and machine learning workloads using AWS SageMaker and Amazon Bedrock.
• Support Retrieval-Augmented Generation (RAG) and AI-driven analytics use cases.
• Build secure and scalable data foundations for Generative AI initiatives.

Governance & Security

• Implement enterprise data governance and security best practices.
• Design secure data access using IAM, Lake Formation, encryption (KMS), and fine-grained access controls.
• Ensure compliance with organizational security and regulatory standards.
• Establish metadata management, data cataloging, lineage, and governance frameworks.

Performance & Cost Optimization

• Optimize AWS data platforms for performance, scalability, and reliability.
• Apply AWS Well-Architected Framework principles.
• Drive cost optimization through storage lifecycle management, compute optimization, and FinOps best practices.
• Monitor and troubleshoot production data platforms.

Technical Leadership

• Provide technical guidance to engineering and data teams.
• Participate in solution reviews and architecture governance.
• Mentor developers and data engineers on cloud architecture best practices.
• Collaborate with cross-functional teams to deliver high-quality enterprise solutions.

Required Skills

AWS Services

• Amazon S3
• AWS Glue
• AWS Lake Formation
• AWS Glue Data Catalog
• Amazon EMR
• Amazon Redshift
• Amazon Athena
• AWS Lambda
• AWS Step Functions
• Amazon Kinesis
• Amazon MSK (Kafka)
• IAM
• KMS
• CloudWatch

Data Technologies

• Data Lake
• Lakehouse Architecture
• Apache Spark
• PySpark
• SQL
• Python
• ETL / ELT
• Batch & Streaming Data Pipelines
• Data Modeling (Dimensional / Data Vault)
• Apache Iceberg / Delta Lake / Apache Hudi
• Metadata Management
• Data Governance

AI & Analytics

• AWS SageMaker
• Amazon Bedrock
• Machine Learning fundamentals
• RAG Architecture (preferred)
• AI-ready Data Platforms

Architecture

• Solution Architecture
• Cloud Architecture
• Microservices Architecture
• API Integration
• High Availability
• Disaster Recovery
• Performance Optimization
• AWS Well-Architected Framework

Required Qualifications

• 10–15 years of experience in Data Engineering, Data Architecture, or Cloud Platform Engineering.
• Minimum 5+ years of hands-on experience designing enterprise data platforms on AWS.
• Strong experience with modern Data Lake/Lakehouse architectures.
• Expertise in AWS data services, distributed data processing, and analytics platforms.
• Strong understanding of cloud security, governance, and performance optimization.
• Excellent communication and stakeholder management skills.

Preferred Certifications

• AWS Certified Solutions Architect – Associate/Professional
• AWS Certified Data Engineer – Associate
• AWS Certified Machine Learning Engineer (Preferred)
• Databricks Certification (Preferred)

Why Join Us?

• Work on large-scale enterprise data transformation initiatives.
• Architect modern cloud-native analytics and AI platforms.
• Collaborate with highly skilled engineering and product teams.
• Drive innovation using AWS, Generative AI, and modern data technologies.