Senior Data Engineer

Overview

The Consultant will lead a structured assessment and advisory engagement across the client's Data Protection Fleet, covering three core practice areas (Cryptography & Secrets, Data Leakage Prevention, Data Asset Protection), the Data Protection Services Policy and Architecture group, and the horizontal functions of fleet enablement, development, and engineering. The engagement will identify and catalogue AI-enabled opportunities across processes, workflows, service consumption, and engineering delivery, culminating in a target-state roadmap and executive-ready findings report. 

Key Responsibilities

Mobilization & Current-State Assessment

•     Establish engagement plan, governance cadence, interview schedule, and workstream structure

•     Confirm in-scope verticals, stakeholder groups, and required artefacts

•     Conduct stakeholder interviews and working sessions across pillars and functions

•     Document current-state operating model, processes, decision points, and friction points

Domain Coverage

•     Cryptography & Secrets: key/certificate lifecycle, secrets onboarding and rotation, vault operations, privileged secrets handling, service-request fulfilment

•     Data Leakage Prevention: DLP policy/ruleset engineering, alert triage and tuning, governance workflows

•     Data Asset Protection: data scanning operations, permissions/entitlement analytics, DSAR workflow support, remediation coordination

•     Policy & Architecture: standards authoring, architecture review support, control interpretation

•     Fleet Enablement, Development & Engineering: roadmap governance, SDLC standardization, engineering standards, tooling consistency

AI Opportunity Identification & Cataloguing

•     Identify AI-enabled use cases across processes, workflows, and engineering delivery for each in-scope pillar

•     Define opportunities for pillar-specific agents and a cross-pillar orchestration agent

•     Populate and maintain the AI Initiatives Tracker (Innovation Backlog, AI Initiatives Register, Risk & Controls, Benefits Tracking)

•     Map current or recommended AI tooling (e.g., M365 Copilot, GitHub Copilot, Claude Code, ChatGPT) to each use case

Feasibility, Controls & Roadmap

•     Assess technical feasibility, control requirements, and data-handling implications for prioritized use cases

•     Define target-state operating model, human-in-the-loop points, and governance forums

•     Prioritize opportunities and build a phased implementation roadmap (near/medium/long-term)

Executive Reporting & Knowledge Transfer

•     Prepare executive-ready findings report and leadership presentation

•     Lead validation workshops and readout/knowledge-transfer sessions with client stakeholders

Required Qualifications

•     Senior-level consulting experience in data security, data protection, or cybersecurity advisory engagements, ideally within Tier-1 financial services

•     Working knowledge across two or more of: cryptography/secrets management (e.g., HashiCorp Vault, PKI), DLP platforms, data discovery/classification and scanning tools, or security architecture and policy

•     Demonstrated experience identifying and scoping AI/automation opportunities within enterprise operating models

•     Strong stakeholder management skills; comfortable leading interviews, workshops, and executive readouts

•     Experience producing operating-model documentation, use-case catalogues, and roadmap artifacts

Preferred Qualifications

•     Prior experience with AI initiative tracking/governance frameworks (risk & controls, benefits tracking)

•     Familiarity with enterprise AI tooling landscape (Copilot Studio, GitHub Copilot, Claude Code, agent orchestration)

•     Background in large-scale financial services technology or security transformation programs