Sr Associate, Data Transformation & Governance

We need to output HTML fragment with sections: Use

for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes Position Summary (we can map to About the role). Essential Duties & Responsibilities -> Responsibilities. Qualifications & Requirements -> Qualifications (maybe also Requirements). There's also Preferred Experience (could be part of Qualifications or separate Skills? Might be considered Skills). There's Success Measures (maybe not a standard heading; we could include as Responsibilities or separate? Not in list; we should not create new headings not in allowed list. So we can incorporate success measures into Responsibilities or maybe omit if not fitting. The instructions: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text. So we need to decide which sections we have content for. We have About the role (position summary). Responsibilities (essential duties). Qualifications (qualifications & requirements). Skills (maybe preferred experience and success measures could be considered skills). Benefits, Pay, Schedule: not present. So we omit those. We must not repeat job title as heading. Also not include Job ID etc. We need to use

• for any list of duties/requirements/benefits, and

  for prose. We need to preserve all substantive information; do not invent or summarize away detail. So we need to include the content from the posting, but we can format as lists where appropriate. We need to strip boilerplate: cookie/navigation/legal/EEO etc. Not present. We need to output only HTML fragment. Thus structure:

  About the role

  ... position summary ...

  Responsibilities

  • ... each duty ...
  ...

  Qualifications

  • ... each qualification ...
  ...
  Maybe also

  Skills

  for preferred experience and success measures? Could treat as Skills. The posting includes "Preferred Experience" bullet list and "Success Measures". Those could be considered Skills or maybe we can put them under Qualifications as additional bullet points. But Qualifications already has required qualifications; we could add a separate Skills section for preferred experience and success measures. The instructions: Prefer a few substantive sections over many thin ones. So maybe combine Preferred Experience and Success Measures into Qualifications or Skills. Since we already have Qualifications, we could add a Skills section for preferred experience and success measures. But we need to decide. Better: Have Qualifications (required) and Skills (preferred). That seems reasonable. Thus:

  Skills

  • Preferred Experience items...
  ...
  And also include Success Measures as maybe part of Skills? Could be separate but we don't have a heading for that. Could incorporate under Skills as bullet points. We must not invent headings not in list. Skills is allowed. Thus we will have About the role, Responsibilities, Qualifications, Skills. Now we need to extract the content. Position Summary paragraph: "Grant Thornton GTech’s vision is centered around enabling scalable, secure, and repeatable data transformation capabilities that support enterprise transformation, mergers and acquisitions, and modern analytics. The Data Transformation & Governance function is responsible for embedding governance, quality, stewardship, compliance, and data standards into transformation initiatives so that data from acquired companies is accurate, secure, compliant, and ready for analytics and business decision-making. Scope extends well beyond structured data. Every acquisition arrives with records held in mailboxes, personal and shared file storage, collaboration sites, chat history, service management platforms, and line-of-business applications, alongside the structured data in HR, finance, and client systems. Much of the firm’s retention and legal exposure sits in that unstructured content rather than in the database tables. This function is expected to see the whole estate, catalog it, determine how each category should be handled, and advise the integration teams accordingly. The Senior Associate, Data Transformation & Governance will support governance activities for acquired-company data integration, helping embed governance principles into data migration, integration, modernization, archival, and analytics enablement efforts. The role carries hands-on responsibility for the inventory, classification, and documentation work that governance decisions depend on, across both structured systems and unstructured content. It works with business stakeholders, data owners and stewards, Data & Analytics, Enterprise Architecture, Security, Privacy, Legal and Risk, application teams, and implementation partners to document governance requirements, support data quality and readiness activities, maintain stewardship materials, and help deliver trustworthy, governed, and usable data assets." We need to preserve all substantive information; we can keep as a paragraph. Now Responsibilities: list of Essential Duties & Responsibilities. We need to extract each bullet (they are sentences separated by periods). We'll create
• for each duty. Let's list them: - Support the application and maintenance of enterprise data governance frameworks for acquired-company integration, including standards, roles, ownership expectations, stewardship routines, escalation paths, and performance metrics. - Assist with embedding governance requirements into data transformation initiatives, including data migration, integration, modernization, archival, reporting, and analytics enablement activities. - Build and maintain the data estate inventory for assigned acquisitions, covering structured application data alongside mailboxes, file storage, collaboration sites, chat and meeting content, service management records, and line-of-business repositories. - Catalog acquired-company content by category, sensitivity, ownership, business purpose, and disposition, and keep that inventory current as discovery progresses. - Prepare handling recommendations for each content category and provide them to tenant consolidation, application, service management, and end user technology teams in a form they can act on during migration planning. - Support review of unstructured and semi-structured content for regulated, privileged, personal, and client-confidential material, and document the handling, access, and protection requirements that result. - Track identification and assignment of accountable data owners for acquired-company data domains, maintain ownership documentation, and flag data domains where ownership has not been established. - Prepare and maintain approval records for new or materially changed use of data, and for external sharing and third-party access, so the approval trail is complete and traceable. - Identify data appearing in the environment without established ownership, registration, or approval, and route it for review. - Apply enterprise retention categories to acquired-company data and content, distinguishing records that must be retained from working copies, duplicates, and transient content, and escalate items that do not classify cleanly. - Document retention periods, retention triggers, and disposal timing for acquired-company data and archived datasets, and track upcoming disposal eligibility. - Support defensible disposal activities by preparing schedules, gathering approvals, and capturing evidence of completion. - Verify legal hold and business hold status before disposal, decommissioning, or archival activity proceeds, and maintain records of holds applicable to acquired-entity data through to release. - Document circumstances that extend retention beyond standard periods, including inherited contractual commitments, audit and investigation activity, and content with long-term business value, and prepare exception or extension requests where requirements cannot be met. - Support coordination with service line quality and risk stakeholders on which acquired-entity records must be retained to satisfy professional standards for audit, tax, and advisory work, and reflect those determinations in working documentation. - Capture jurisdictional differences across assigned entities, including local privacy, data residency, and statutory retention requirements, and flag conflicts with enterprise requirements. - Support data quality and standardization activities by documenting data quality rules, profiling outputs, root-cause findings, remediation actions, reconciliation expectations, and quality gate evidence. - Help standardize data definitions, formats, critical data elements, metadata, lineage information, and ownership documentation across acquired-company sources and enterprise target-state platforms. - Maintain catalog and business glossary entries for acquired-company data domains so consumers can determine meaning, context, provenance, and appropriate use. - Support data stewardship activities by maintaining steward and owner documentation, tracking assigned stewardship actions, coordinating follow-ups, and helping promote accountability for data assets. - Assist with adoption and use of governance technologies such as data catalog, metadata management, lineage, data quality, master data management, and data issue management tools. - Work with IT, data platform teams, and vendors to document governance technology requirements, support pilots, validate tool outputs, and contribute to rollout materials. - Collaborate with Legal, Privacy, Risk, Compliance, and Security teams to help document data protection controls, classification, access control, masking, retention, and disposal requirements. - Prepare governance reporting and metrics, including data quality scores, policy adherence, stewardship engagement, remediation progress, issue aging, readiness gate status, and governance maturity inputs. - Create dashboards, status updates, meeting materials, and issue logs that communicate governance progress, risks, readiness, decisions needed, and business value. - Facilitate or support cross-functional working sessions to align transformation activities with governance requirements and ensure data decisions are traceable and documented. - Support source-to-target mapping, lineage, reconciliation, data issue resolution, and integration readiness activities during acquired-company data transformation efforts. - Promote consistent governance practices by communicating expectations, maintaining documentation, and helping teams understand the value of trusted, compliant, and reusable data. - Identify opportunities to improve governance work products, data quality controls, stewardship routines, metadata practices, reporting, and repeatable transformation delivery practices. - Other duties as assigned. Now Qualifications & Requirements: list: - 4+ years of experience in data governance, data transformation, data management, data quality, data integration, records and information management, data privacy and compliance, analytics, or related enterprise technology roles. - Experience supporting data governance activities within data migration, integration, modernization, archival, analytics, or large-scale transformation programs. - Exposure to governing unstructured and semi-structured content alongside structured data, including mail, file storage, collaboration platforms, and service management records. - Working knowledge of records retention practice, including retention categories, retention triggers, disposal timing, and the evidence required to support disposal. - Understanding of legal hold and preservation obligations and their effect on routine disposal activity. - Experience supporting merger, acquisition, divestiture, or acquired-company technology and data integration initiatives preferred. - Working knowledge of data governance frameworks, data ownership, data stewardship, critical data elements, data quality management, metadata, lineage, catalog and glossary practice, retention, and governed data delivery. - Experience documenting data quality rules, profiling outputs, remediation actions, reconciliation activities, issue tracking, and readiness metrics. - Familiarity with data governance technologies such as data catalogs, metadata management platforms, lineage tools, MDM platforms, data quality tools, workflow tools, or data issue management capabilities. - Understanding of data protection and compliance concepts, including privacy, classification, access management, masking, retention, and internal policy controls. - Awareness of retention and documentation requirements arising from professional standards in an audit, tax, or advisory environment, or comparable regulated experience. - Ability to work with business and technology stakeholders, translate governance concepts into practical documentation, and support alignment across teams. - Strong organizational, analytical, documentation, communication, facilitation, and stakeholder follow-up skills. - Bachelor’s degree in Information Systems, Data Analytics, Business, Computer Science, Engineering, or related field required; relevant data governance, privacy, records management, security, project management, or cloud and data certifications preferred. Now Preferred Experience (we can treat as Skills): - Experience operating in a professional services, consulting, accounting, or complex global enterprise environment. - Experience with governance and data platform tools such as Microsoft Purview, Collibra, Informatica, Alation, Snowflake, Power BI, ServiceNow, or comparable technologies. - Experience with retention, classification, or eDiscovery capabilities across mail, file storage, and collaboration platforms. - Experience supporting data archival, historical data retention, legacy system decommissioning, or compliance-driven data preservation initiatives. - Experience contributing to governance playbooks, stewardship operating materials, data readiness checklists, data quality scorecards, issue management routines, and dashboard reporting. - Experience working with implementation partners, systems integrators, vendors, or consulting teams within transformation programs. - Experience supporting cross-functional governance forums, data decision groups, or working sessions with business, technology, risk, legal, privacy, and security stakeholders. - Exposure to cross-border data handling, including