Data Solution Architect Lead

Role Summary

We're seeking an experienced Delivery Lead to drive the data lifecycle management agenda, blending delivery leadership with data/application analysis.

This role will involve leading cross-functional teams, running workshops, mapping processes, prioritizing and governing backlogs, and ensuring timely, high-quality implementation of data retention and risk-mitigation capabilities.

1. Delivery Leadership & Governance

• Own end-to-end delivery (scope, schedule, 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.

• Lead investigations of applications and their data to assess risks, retention needs, and compliance.
• 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 analyze stakeholder requirements for effective data risk management.

• 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.

• 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.

• 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.

• 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.
• Track down and engage appropriate stakeholders and technical SMEs; experienced in requirements/ideation/solution workshops.
• Strong technical/engineering awareness (data preferred), able to understand architecture, integration points, and application landscapes.
• Highly organized, self-motivated, detail-oriented; excellent at prioritization, dependency management, and execution.
• Proactive, analytical thinker who finds opportunities in constraints.
• Strong understanding of Scrum and Kanban; proven facilitation and coaching in agile ceremonies.

• A minimum of 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.
• Exposure to Azure/AWS/GCP data platforms (e.g., ADLS/S3, ADF/Glue, Synapse/BigQuery, Databricks/Spark).
• Knowledge of data governance/privacy (e.g., GDPR, retention schedules, information classification).
• Experience in telecom or large-scale consumer services.