Enterprise Data Delivery Lead – Azure & Databricks

M&G; Stirling; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Pension up to 18%

Share Save & Incentive Plan

38 days annual leave

Inspiring Families policy

Private Healthcare & Life Assurance

Job summary

M&G is seeking a Technical Delivery Manager (Data) to lead end-to-end delivery of data initiatives across Enterprise Data, coordinating business, technology and delivery teams to shape outcomes and ensure secure, well-governed data solutions.

The role covers cloud data platforms and collaboration with data engineering, architecture, testing, security, finance and operations, with emphasis on planning, risk management and production readiness.

Qualifications

• Strong technical delivery capability in complex data, cloud or platform environments.
• Knowledge of project and delivery methods such as Agile, Scrum, Waterfall or hybrid approaches.
• Understanding of data delivery concepts, including ingestion, integration, ETL/ELT, data modelling, reporting, analytics, data quality and data governance.
• Working knowledge of cloud data platforms and data delivery tooling, including Azure, Databricks, Azure DevOps, Jira or similar tools.
• Ability to manage cross-functional delivery teams, including internal colleagues and external suppliers.
• Strong stakeholder management skills, with the ability to communicate clearly with technical and non-technical audiences.
• Strong planning, prioritisation and problem-solving skills, with the confidence to manage risks, dependencies and trade-offs.
• Knowledge of risk, control, compliance and data protection considerations in a regulated environment.

Responsibilities

• Own end-to-end delivery for assigned data initiatives, from inception and planning through build, test, release, warranty and handover to support.
• Create and maintain integrated delivery plans, including scope, milestones, dependencies, risks, actions, issues and decisions.
• Establish clear delivery governance, including reporting, quality gates, change control, RAID management and escalation routes.
• Work closely with Product Owners, business leads, architects, engineers, testers, security, risk, finance and operations teams to deliver agreed outcomes.
• Support delivery across cloud data platforms, including Azure and Databricks, making sure requirements, priorities and outcomes are clear and traceable.
• Manage delivery finances, forecasts, benefits tracking and resource planning where applicable.
• Define and manage acceptance criteria, delivery controls and operational readiness for data platforms and data products.
• Make sure data protection, access control, auditability, lineage, metadata and wider control requirements are considered as part of delivery.
• Lead supplier and third-party delivery where relevant, including statements of work, delivery commitments, onboarding, offboarding, service expectations and performance.
• Maintain clear, concise and timely communication with stakeholders, including senior stakeholders, delivery teams and control functions.
• Identify, manage and escalate risks, issues and dependencies early, with clear options and recommendations.
• Support smooth transition into BAU, making sure monitoring, alerting, support processes, runbooks and ownership are understood.
• Drive continuous improvement across delivery practices, including templates, playbooks, retrospectives, delivery metrics and ways of working.
• Role-model collaborative, transparent and outcome-focused delivery across cross-functional teams.

Skills

Technical delivery leadership

Data platform delivery

Azure and Databricks

Agile and hybrid delivery

Delivery governance

Stakeholder management

Tools

Azure

Databricks

Azure DevOps

Jira

Job description

M&G is seeking a Technical Delivery Manager (Data) to lead end-to-end delivery of data initiatives across Enterprise Data, coordinating business, technology and delivery teams to shape outcomes and ensure secure, well-governed data solutions.

The role covers cloud data platforms and collaboration with data engineering, architecture, testing, security, finance and operations, with emphasis on planning, risk management and production readiness.