Shyftlabs5mo ago

Technical Delivery Manager

NoidaFull-Timemid

OtherProject & Program ManagementDelivery ManagerTechnical Delivery Manager

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Overview

Position Overview We are seeking a highly driven Technical Delivery Manager (TDM) who excels at bridging Product, Engineering, QA, DevOps,

Technical Tools

OtherProject & Program ManagementDelivery ManagerTechnical Delivery Manager

Position Overview

We are seeking a highly driven Technical Delivery Manager (TDM) who excels at bridging Product, Engineering, QA, DevOps, and Commercial teams to ensure seamless execution and smooth production releases. This role is focused on owning the ‘last mile’ of delivery, taking features from post-QA refinement through production deployment, stabilization, and post-launch support.

You will be the single owner of delivery across all Carter workstreams, coordinating multiple teams, managing dependencies, and ensuring every feature moves predictably from development to production without delays. If you thrive in fast-paced, high-ownership environments and bring both technical depth and delivery rigor, this role is for you.

ShyftLabs is a growing data product company founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions designed to accelerate business growth across industries by focusing on innovation, efficiency, and measurable impact.

Own end-to-end delivery for all Carter workstreams, ensuring features move smoothly from scoping to production deployment.

Maintain visibility into progress, risks, and blockers across engineering, QA, and DevOps teams.

Translate product requirements into actionable technical plans and timelines.

Coordinate cross-functional communication across backend, frontend, data, QA, DevOps, and product.

Define and manage predictable release schedules and deployment calendars.

Own production deployment activities, including go/no-go decisions and rollback planning.

Run daily standups, sprint planning, sprint reviews, and retros as needed.

Hold teams accountable to delivery timelines while removing execution barriers.

Track multi-track workstreams and communicate dependencies across interconnected systems.

Prevent prioritization conflicts and ensure alignment across all delivery paths.

Identify delivery bottlenecks and implement lightweight, efficient process improvements.

Establish SOPs for QA handoffs, deployment, readiness checks, and release workflows.

Drive continuous improvement through post-mortems and feedback loops.

Maintain dashboards reporting delivery metrics (velocity, cycle time, defect rates, deployment success, etc.).

Provide weekly delivery summaries to leadership, highlighting progress, risks, and mitigations.

Conduct Production Readiness Reviews (PRRs) and ensure proper monitoring, alerting, and rollback steps.

Lead post-launch stabilization and rapid response during the first 48 hours of release.

Act as incident commander for production issues related to new releases.

Lead post-incident reviews (PIRs) and ensure preventive measures are implemented.

Track and report on production stability and performance of recently shipped features.

Strong technical background with understanding of APIs, microservices, data workflows, and cloud deployments.

Experience with ad tech, real-time bidding (RTB), or distributed systems (preferred but not required).

8+ years in Technical Delivery Management, Technical Program Management, or Engineering Project Management.

Distributed architecture: monolith to micro services, cloud-native principles, containers & orchestration, Infrastructure as a code, multi-tenancy models, etc.

Data architecture: data modeling concepts, data engineering concepts, reporting and analytics

DevOps and CI/CD architecture: Release management, deployment strategies (blue/green or canary or rolling), automation

Scalability and performance architecture concepts: Scaling strategies, caching strategies, capacity planning, observability, etc.

Exposure to AI/ML or data-driven product environments, with familiarity in coordinating with data science and data engineering teams, understanding ML workflows and model deployment pipelines, and awareness of emerging technologies such as Generative AI and modern data platforms.

Proven success managing multiple complex workstreams in fast-paced environments.

Strong experience with Agile methodologies, SDLC, and release management.

Experience scaling delivery processes in high-growth or startup environments (preferred).

Exceptional communication and cross-functional coordination skills.

Strong ownership mindset and ability to bring clarity to ambiguous situations.

Calm under pressure with excellent risk and dependency management abilities.

Highly organized, detail-oriented, and data-driven in decision making.

Ability to communicate effectively with both technical and non-technical stakeholders.