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. You'll 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 You'll Own
Practice Strategy & Roadmap
Define the multi-year vision and roadmap for atQor's 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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