Delivery Lead - Data Analytics

The Delivery Lead will be responsible for the end-to-end delivery of multiple Data and Analytics projects, products, and workstreams within a large enterprise setting. This role requires a hands-on understanding of PySpark and Microsoft Fabric, combined with strong agile delivery expertise. The ideal candidate will effectively manage complex dependencies, governance frameworks, vendor relationships, stakeholder communications, and executive-level reporting to ensure successful project outcomes.

Key Responsibilities

- Own the complete delivery lifecycle of multiple Data and Analytics initiatives, ensuring alignment with agreed scope, timelines, quality standards, and business objectives.
- Coordinate cross-functional teams including Data Engineering, Business Intelligence, Analytics, Data Architecture, Platform, and Production Support to drive seamless collaboration.
- Utilize hands-on knowledge of PySpark and Microsoft Fabric to grasp technical delivery requirements, identify dependencies, assess risks, and address challenges proactively.
- Manage agile delivery processes such as backlog grooming, sprint planning, sprint governance, release planning, user acceptance testing (UAT), deployment, and post-production hypercare support.
- Develop and maintain integrated delivery plans that encompass milestones, dependencies, resource allocation, risks, assumptions, issues, and key deliverables.
- Maintain comprehensive RAID logs, dependency trackers, delivery metrics, action logs, and prepare executive-level status reports to keep stakeholders informed.
- Identify and resolve delivery risks, blockers, and cross-workstream dependencies through timely escalation and collaboration.
- Work closely with Product Owners, Engineering Leads, Architects, Business Stakeholders, and Support teams to maintain delivery alignment and momentum.
- Coordinate UAT activities, defect resolution, release readiness, production deployment, and hypercare support to ensure smooth transitions.
- Ensure all delivery activities comply with enterprise governance, security, operational, audit, and change control requirements.
- Facilitate effective documentation, knowledge transfer, operational readiness, and transition of delivered solutions into support teams.

Required Qualifications

- Over 10 years of experience in Data and Analytics delivery, technology delivery, data engineering, or related fields, with a proven track record of leading complex enterprise-scale initiatives.
- Hands-on working knowledge of PySpark and Microsoft Fabric, enabling engagement with modern data and analytics solutions.
- Strong experience managing delivery across multiple Data and Analytics products, workstreams, squads, or concurrent projects.
- Practical expertise in agile delivery methodologies, including backlog management, sprint governance, release planning, UAT, deployment, and hypercare.
- Demonstrated ability to maintain integrated delivery plans, RAID logs, dependency management, delivery metrics, and executive-level reporting.
- Proven success coordinating multidisciplinary teams across Data Engineering, BI, Analytics, Architecture, Platform, and Support functions.
- Experience managing vendor resources, including capacity planning, onboarding, offboarding, continuity, and knowledge transfer.
- Skilled in leading Data and Analytics delivery teams for enterprise-scale solutions, preferably within a matrix organizational structure.
- Solid understanding of data governance, data lineage, data quality, semantic models, and modern data platform architectures.
- Strong capability to translate technical delivery requirements into clear plans, milestones, risk assessments, dependencies, and measurable business outcomes.

Preferred Qualifications and Benefits

- Relevant certifications such as Agile, PMP, PRINCE2, SAFe, Scrum Master, or ITIL are highly desirable.
- Experience working in FMCG or other fast-paced global enterprise environments is advantageous.

This role offers the opportunity to lead critical data and analytics delivery initiatives within a dynamic enterprise, collaborating with diverse teams and driving impactful business outcomes through innovative data solutions.