Join NTT DATA as an Industry Consulting Consultant and contribute to innovative cloud database migrations. This role focuses on leveraging strong database expertise, cloud architecture knowledge, and AI tooling to ensure secure, reliable, and low-downtime migrations to AWS. You'll be instrumental in assessing on-premises workloads, planning complex migrations, and designing robust AWS target environments.

Key responsibilities include assessing existing on-premises databases and planning both homogeneous and heterogeneous migrations to AWS. You will be converting schemas, stored procedures, and SQL across different database engines. Designing secure AWS target architectures (RDS, Aurora, EC2), executing cutover and rollback plans, and automating deployments using Infrastructure as Code are also critical aspects of this role. Post-migration, you'll focus on performance tuning and monitoring.

This position involves advanced utilization of AI and Machine Learning tools. You will use Generative AI/LLMs for translating proprietary SQL dialects and AI-assisted coding tools for generating, explaining, and debugging migration scripts. AI-based assessment and discovery tools will aid in workload analysis and target sizing, while AI-driven performance monitoring will detect anomalies and optimize post-migration performance. A strong validation mindset is crucial to ensure accuracy and identify potential AI-generated errors.

Core technical requirements include deep expertise in databases such as Oracle, SQL Server, MySQL, PostgreSQL, and Db2, along with strong SQL and tuning skills. Experience with AWS migration services (DMS, SCT) and AWS core services (RDS, Aurora, EC2, S3) is essential. A solid understanding of cloud foundations, including VPC, IAM, networking, and the Well-Architected Framework, is expected. Proficiency in security best practices (KMS, SSL/TLS, least-privilege IAM) and compliance standards (GDPR, HIPAA, PCI-DSS) is also required. Automation skills with Terraform/CloudFormation and scripting languages like Python, Bash, or PowerShell, coupled with CloudWatch monitoring, are necessary.

For AI-related skills, candidates should possess experience with Generative AI/LLMs, AI-assisted coding tools, ML-based assessment tools, and AI-driven performance monitoring. Strong prompt engineering skills for effective AI interaction and a diligent validation mindset to identify AI errors are key. Familiarity with downstream AI/ML pipelines, data lakes, and vector databases is beneficial. Soft skills such as problem-solving, clear communication, and project management awareness are highly valued. AWS certifications or enterprise migration experience are considered advantages.