Technical Scrum Master

Job Summary

The Technical Scrum Master will lead agile delivery for the AWS Policy Master engineering pod and serve as the execution bridge among product owners, business and policy SMEs, solution architecture, data engineering, API, database, DevSecOps, and quality teams. The role combines strong Scrum facilitation with sufficient AWS and data-engineering fluency to manage technical dependencies, remove impediments, maintain delivery transparency, and drive predictable releases across the S3LambdaSQSAuroraAPI flow. The individual will not act as the solution architect, but must be comfortable challenging plans, surfacing delivery risk, and translating technical progress into business-ready status.

Location: Bangalore, Karnataka, India.

Required Skills and Experience

• 810 years of overall technology delivery experience, including at least 4 years as a Scrum Master or agile delivery lead for data, cloud, integration, or application-modernization teams.
• Strong working knowledge of Scrum and Kanban practices, sprint planning, backlog refinement, daily stand-ups, reviews, retrospectives, release planning, velocity, capacity, and dependency management.
• Experience coordinating multidisciplinary engineering teams spanning cloud data pipelines, APIs or microservices, database engineering, DevSecOps, automation testing, and production support.
• Practical understanding of AWS delivery concepts - S3, Lambda, SQS, EventBridge, Aurora PostgreSQL, API Gateway, IAM, CloudWatch, CI/CD, and infrastructure as code - to facilitate informed technical planning and risk discussions.
• Demonstrated ability to manage cross-team dependencies, RAID items, critical paths, nonfunctional requirements, environment readiness, testing gates, and release or cutover activities.
• Hands-on experience with Jira and Confluence or equivalent agile lifecycle tools; ability to create actionable dashboards and concise executive status reports.
• Strong facilitation, conflict-resolution, stakeholder-management, written communication, and coaching skills; comfortable working across onsite and offshore teams and multiple time zones.
• Experience in insurance, policy administration, operational data stores, data mastering, or regulated financial-services programs is strongly preferred.
• Scrum certification such as CSM, PSM, SAFe Scrum Master, or PMI-ACP is preferred; AWS Cloud Practitioner or similar foundational cloud certification is an advantage.

Duties

• Facilitate sprint ceremonies and ensure each sprint has clear objectives, prioritized stories, acceptance criteria, dependencies, estimates, and accountable owners.
• Partner with the Product Owner and technical leads to maintain a healthy backlog covering ingestion, validation, buffering, transformation, canonical policy data, Aurora persistence, APIs, observability, security, and reliability.
• Build and maintain integrated sprint and release plans across AWS data engineering, Aurora data modeling, API engineering, DevSecOps, testing, business SMEs, and dependent source or consumer teams.
• Identify, track, and remove delivery impediments; escalate architecture, access, environment, data, security, vendor, or dependency blockers with clear impact and resolution dates.
• Monitor sprint predictability, throughput, carryover, defect trends, test progress, technical debt, and release readiness; convert metrics into practical corrective actions rather than administrative reporting.
• Coordinate technical design reviews, story readiness, definition-of-done adherence, nonfunctional requirement coverage, test evidence, production-readiness reviews, and go/no-go checkpoints.
• Facilitate decision-making and conflict resolution while preserving clear accountability among the Product Owner, architects, engineering leads, and business stakeholders.
• Drive continuous improvement through retrospectives, root-cause follow-up, dependency reduction, automation opportunities, and consistent agile engineering practices.
• Provide concise weekly status covering accomplishments, upcoming milestones, risks, decisions, dependencies, staffing, and any impact to scope, schedule, quality, or cost.
• Support cutover, hypercare, incident triage, and post-release reviews to ensure operational learning is incorporated into subsequent sprints.