Delivery Lead

Key Responsibilities

1) Delivery Leadership & Governance

Own end‑to‑end delivery (scope, schedule, budget, quality) for the Data

Lifecycle/Retention workstream(s).

Establish and run delivery governance: RAID (Risks, Assumptions, Issues, Dependencies),

change control, approvals, and compliance gates.

Coordinate cross‑functional squads (engineering, architecture, security, risk, legal,

product, business) to meet milestones and value outcomes.

Manage vendor/partner deliverables and ensure contract/SLA adherence where

applicable. Provide clear, proactive communications—status, decisions, and escalations—to

stakeholders and leadership.

2) Data & Application Analysis Lead investigations of applications and their data to

assess risks, retention needs, and compliance (spanning brands, segments, channels).

Collaborate with application owners and technical SMEs to understand data

flows, integration points, business/technology processes, and their impact on data

assets.

Provide reporting, visualizations, and insights based on data analysis to inform design

decisions.

Gather and analyse stakeholder requirements for effective data risk management.

3) Solution Design & Delivery

Work with solution architects, product managers, and business stakeholders to design,

develop, and evaluate data retention and management solutions.

Identify opportunities to enhance data risk management through automation and

technology.

Translate requirements into Epics, User Stories, Acceptance Criteria, and Test

Cases in Jira; keep the backlog prioritized with clear timelines.

Break down deliverables with architects/engineers into estimable increments;

enable incremental value delivery.

Collaborate with engineers and testers to ensure deliverables meet Definition of

Done and acceptance criteria; provide actionable feedback.

4) Agile Facilitation & Ways of Working

Facilitate team ceremonies: daily stand‑ups, sprint planning, reviews/demos,

retrospectives, and backlog refinement.

Document outcomes from workshops/meetings with clarity and convert insights

into actionable backlog items.

Champion continuous improvement in throughput, flow efficiency, and quality.

5) Risk, Compliance & Quality

Ensure solutions align with data policies (retention, privacy, information security),

regulatory obligations, and internal standards.

Define and monitor quality measures (test coverage, defect leakage, audit readiness).

Partner with Security, Risk, and Legal on data risk mitigation, audit artifacts, and

evidence.

6) Stakeholder Management & Change Enablement

Engage and align diverse stakeholders—from engineers to executives—through

structured communications and decision forums.

Prepare change impact assessments, training/enablement plans, and adoption metrics

for business readiness.

Stakeholder Engagement: Able to track down and engage appropriate stakeholders

and technical SMEs; experienced in requirements/ideation/solution workshops.

Technical Fluency: Strong technical/engineering awareness (data preferred), able to

understand architecture, integration points, and application landscapes.

Delivery Mindset: Highly organized, self‑motivated, detail‑oriented; excellent

at prioritization, dependency management, and execution.

Problem Solving: Proactive, analytical thinker who finds opportunities in constraints.

Agile Expertise: Strong understanding of Scrum and Kanban; proven facilitation and

coaching in agile ceremonies.

Required Qualifications & Experience

8–12 years of total experience, including 4–6 years leading data or application

delivery initiatives in complex enterprises.

Demonstrated success delivering data management/data retention or adjacent data

governance/risk management solutions.

Hands‑on experience with Jira/Confluence (or similar) for backlog and delivery

governance.

Proven ability to manage RAID, cross‑team dependencies, and executive‑level reporting.

Strong communication and documentation skills; ability to convert discovery into clear,

testable work items.

Nice‑to‑Have

Exposure to Azure/AWS/GCP data platforms (e.g., ADLS/S3, ADF/Glue,

Synapse/Big Query, Databricks/Spark).

Knowledge of data governance/privacy (e.g., GDPR, retention schedules, information

classification).

Experience in telecom or large‑scale consumer services.

Certifications: Scrum Master

(PSM/CSM), Prince2/PMI, SAFe, Azure/AWS fundamentals.

Tools & Technologies

Delivery: Jira, Confluence, MS Project/Smartsheet, Miro.

Visualization/Reporting: Power BI/Tableau, Excel.

Collaboration: MS Teams, SharePoint.

Data (nice‑to‑have): Azure Data Factory, Databricks, Synapse, SQL, Python (for

analysis/validation)