Technical Delivery Team Manager

Technical Delivery Manager – Data & Analytics and AI

About the Role

atQor is looking for a Technical Delivery Manager – Data & Analytics and AI to head our engineering vertical across Microsoft Fabric, Data Engineering, Analytics, Databricks, and AI Agents. You will own the practice end-to-end — from strategy and capability building to delivery excellence, P&L health, and pre-sales enablement.

This is a senior leadership role reporting directly to the Head of Delivery. You will be the single point of accountability for everything the practice ships — data ingestion pipelines, transformation frameworks, lakehouse architectures, BI and visualization solutions, and the next generation of agentic AI applications. Youll lead a team of architects, data engineers, BI developers, and AI engineers, and partner closely with Sales, Pre-sales, Practice Leads of adjacent verticals, and customers to grow the business.

What Youll Own

Practice Strategy & Roadmap

Define the multi-year vision and roadmap for atQors Data & Analytics and AI practice spanning Microsoft Fabric, Azure Data Services, Databricks, Power BI, and AI / Agentic AI.

• Identify emerging technologies, evaluate platforms, and decide where atQor invests — solutions, accelerators, IP, and partnerships.
• Build and maintain reusable assets, reference architectures, and solution accelerators that shorten time-to-value for customers

Capability, Capacity & Hiring

• Build the org design, role ladders, and skill matrix for the practice — across data engineering, analytics, AI, and platform engineering.
• Own the hiring plan; partner with Talent Acquisition to recruit, evaluate, and onboard high-caliber talent.
• Drive certification and upskilling programs across Fabric, Databricks, Azure Data Engineer, AI Engineer, and Microsoft AI / OpenAI tracks.
• Forecast capacity against the demand pipeline; balance bench, billable, and growth investment.

Delivery Quality & CSAT

• Be the single point of accountability for delivery health across all practice engagements.
• Establish delivery standards, code quality gates, architecture review boards, and customer success rituals.
• Drive customer satisfaction (CSAT/NPS) and proactively manage escalations on critical accounts.
• Run delivery reviews, post-mortems, and continuous improvement cycles to reduce defects, rework, and delivery slippage.

Pre-Sales & Estimation

• Own the estimation framework for the practice — effort, team mix, timeline, and risk contingency.
• Review and approve all proposals, SOWs, and technical responses originating from the practice

People — 1:1s, Growth & Retention

• Run a strong people operating system — regular 1:1s, career conversations, performance reviews, and growth plans.
• Build a culture of technical excellence, ownership, and customer-first thinking across the practice.
• Identify high-potential talent; create stretch opportunities and succession plans for key role.

Technical Scope

The practice spans the full data and AI value chain:

• Data Ingestion — Azure Data Factory, Fabric Data Factory, Synapse Pipelines, event streaming (Event Hubs, Kafka), real-time ingestion patterns.
• Data Transformation & Storage — Microsoft Fabric (OneLake, Lakehouse, Warehouse), Databricks (Delta Lake, Unity Catalog, workflows), dbt, Spark, medallion architectures.
• Visualization & BI — Power BI (enterprise semantic models, paginated reports, embedded), Fabric Direct Lake, Real-Time Analytics.
• AI & Agentic AI — Azure OpenAI, Azure AI Foundry, Copilot Studio, Semantic Kernel, LangChain / LangGraph, RAG architectures, multi-agent orchestration, AI evaluation and guardrails.
• Governance & Platform — Microsoft Purview, Unity Catalog, security, lineage, cost management, and FinOps practices.

What You Bring

Experience

• 14+ years of overall experience in data, analytics, and cloud engineering, with at least 5–6 years in a leadership / practice-head role.
• Proven track record of building and scaling a Data / AI / Cloud practice in a services or consulting environment.
• Hands-on depth in the Microsoft Data & AI stack (Fabric, Synapse, Azure Data Services, Power BI, Azure OpenAI) and Databricks.
• Demonstrated experience delivering enterprise-grade AI / GenAI / agentic AI solutions in production.
• Desired experience owning P&L, utilization, and pre-sales
• People Management Experience in a practice of 30+ people.

Skills & Capabilities

• Deep architectural fluency across modern lakehouse, streaming, and AI architectures.
• Strong commercial acumen — comfortable with estimation, pricing, margin management, and deal economics.
• Excellent customer-facing skills — credible with CXOs, Chief Data Officers, and engineering Leaders.
• Ability to balance technical depth with business outcomes
• Familiarity with Agile delivery, DevOps / DataOps / MLOps, and cost-optimization practices on Azure.

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