Senior Project Manager (Data & AI)

London - UK

Monthly Salary: Not Disclosed

Experience Required: 5years

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Overview

The Senior Project Manager will oversee multiple projects within a Data & AI program. This role requires strategic oversight strong leadership and the ability to coordinate across multiple workstreams. The ideal candidate will have extensive experience delivering complex technology programs and will work collaboratively with cross-functional teams to ensure successful delivery against business objectives.

Key Responsibilities

Project Leadership: Manage multiple concurrent projects ensuring alignment with strategic goals and successful delivery of agreed outcomes.
Strategic Planning: Lead end-to-end planning execution and delivery of Data & AI initiatives. Define project scope objectives timelines and success metrics while ensuring the technical feasibility of proposed solutions.
Technical Oversight: Provide hands-on expertise in cloud technologies such as Azure AWS Databricks or Snowflake.
Program Coordination: Act as a central coordination point across complex stakeholder ecosystems including partners and internal teams.
Agile Delivery: Lead Agile delivery processes facilitating key ceremonies such as daily stand-ups sprint planning sprint reviews and retrospectives. Coach teams on Agile principles and remove impediments to progress.
Communication Frameworks: Establish structured communication methods to ensure seamless information flow between business and technical stakeholders.
Resource Management: Lead and manage project resources set clear objectives monitor performance and provide feedback to governing bodies or project boards.
Collaboration: Foster a collaborative environment that bridges technical and business stakeholders ensuring clear understanding of project goals and individual contributions.
Risk Management: Proactively identify assess and mitigate project risks including technical challenges resource constraints timeline delays and data quality issues.
Performance Monitoring: Define and track key performance indicators (KPIs) to monitor project progress team productivity stakeholder satisfaction and partnership effectiveness.

Required Experience & Qualifications

1820 years of experience as a Project Manager with significant expertise in the Data & AI domain.
Proven ability to manage large complex programs with multiple workstreams.
Strong hands-on knowledge of modern cloud platforms and technologies (Azure AWS Databricks Snowflake).
Experience working in Agile environments and leading Agile delivery teams.
Excellent stakeholder management communication and leadership skills.

Preferred Certifications & Skills

Project Management Professional (PMP)
Certified Associate in Project Management (CAPM)
Certified Scrum Master (CSM) or SAFe Scrum Master (SSM)
Azure AI Fundamentals (AI-900) or AWS Certified Cloud Practitioner
Experience managing technology adoption for new business users
Willingness to work onsite up to two days per week

Overview The Senior Project Manager will oversee multiple projects within a Data & AI program. This role requires strategic oversight strong leadership and the ability to coordinate across multiple workstreams. The ideal candidate will have extensive experience delivering complex technology programs...

Overview

Key Responsibilities

Project Leadership: Manage multiple concurrent projects ensuring alignment with strategic goals and successful delivery of agreed outcomes.
Strategic Planning: Lead end-to-end planning execution and delivery of Data & AI initiatives. Define project scope objectives timelines and success metrics while ensuring the technical feasibility of proposed solutions.
Technical Oversight: Provide hands-on expertise in cloud technologies such as Azure AWS Databricks or Snowflake.
Program Coordination: Act as a central coordination point across complex stakeholder ecosystems including partners and internal teams.
Agile Delivery: Lead Agile delivery processes facilitating key ceremonies such as daily stand-ups sprint planning sprint reviews and retrospectives. Coach teams on Agile principles and remove impediments to progress.
Communication Frameworks: Establish structured communication methods to ensure seamless information flow between business and technical stakeholders.
Resource Management: Lead and manage project resources set clear objectives monitor performance and provide feedback to governing bodies or project boards.
Collaboration: Foster a collaborative environment that bridges technical and business stakeholders ensuring clear understanding of project goals and individual contributions.
Risk Management: Proactively identify assess and mitigate project risks including technical challenges resource constraints timeline delays and data quality issues.
Performance Monitoring: Define and track key performance indicators (KPIs) to monitor project progress team productivity stakeholder satisfaction and partnership effectiveness.

Required Experience & Qualifications

1820 years of experience as a Project Manager with significant expertise in the Data & AI domain.
Proven ability to manage large complex programs with multiple workstreams.
Strong hands-on knowledge of modern cloud platforms and technologies (Azure AWS Databricks Snowflake).
Experience working in Agile environments and leading Agile delivery teams.
Excellent stakeholder management communication and leadership skills.