Join NTT DATA as a Data Engineer Advisor, a pivotal role focused on leading agile delivery for an AWS Policy Master engineering pod. This position serves as the central hub for communication and execution, bridging product owners, subject matter experts, architecture, data engineering, and quality assurance teams. The role demands a blend of strong Scrum facilitation and practical AWS/data engineering knowledge to effectively manage technical dependencies, resolve impediments, and ensure transparent, predictable releases across a complex AWS data flow.

While not responsible for solution architecture, the advisor will actively contribute to technical discussions, identify delivery risks, and translate technical progress into clear, business-oriented updates. This is an opportunity to influence innovation and grow within a forward-thinking organization committed to accelerating client success and societal impact.

Facilitate all sprint ceremonies, ensuring clear objectives, prioritized stories, and defined acceptance criteria for each sprint. Partner closely with the Product Owner to maintain a robust backlog that addresses data ingestion, validation, transformation, and persistence layers.

Develop and manage integrated sprint and release plans across AWS data engineering, Aurora data modeling, API engineering, DevSecOps, and testing teams. Proactively identify, track, and resolve delivery impediments, escalating blockers with clear impact assessments and proposed resolutions.

Monitor sprint predictability, defect trends, and release readiness, translating metrics into actionable improvements. Coordinate technical design reviews, story readiness checks, and go/no-go checkpoints for production releases. Drive continuous improvement through retrospectives and automation opportunities.

Provide concise weekly status reports covering accomplishments, upcoming milestones, risks, and dependencies. Support cutover, hypercare, and post-release reviews to integrate operational learnings into future sprints.

A minimum of 8-10 years in technology delivery, with at least 4 years specifically as a Scrum Master or agile delivery lead for data, cloud, or application modernization projects. Strong proficiency in Scrum and Kanban methodologies, including sprint planning, backlog refinement, and dependency management.

Experience coordinating diverse engineering teams involved in cloud data pipelines, APIs, microservices, database engineering, DevSecOps, and automated testing. A solid understanding of AWS services such as S3, Lambda, SQS, EventBridge, Aurora PostgreSQL, API Gateway, IAM, and CloudWatch is essential.

Demonstrated ability to manage cross-team dependencies, critical paths, non-functional requirements, and release activities. Hands-on experience with Jira and Confluence, coupled with strong facilitation, conflict resolution, stakeholder management, and written communication skills, is required. Comfort working with both onsite and offshore teams across multiple time zones is crucial.

While not mandatory, experience in insurance, policy administration, or regulated financial services programs is highly preferred. Agile or cloud certifications are advantageous.