Manager, Data & Analytics

We need to output HTML fragment with sections: About the role (position summary), Responsibilities (Essential Duties & Responsibilities), Qualifications (Qualifications & Requirements), maybe Preferred Experience? Could be part of Qualifications? The instructions: Use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Include a section only when posting has real specific content. We have: - Position Summary: we can put under About the role. - Essential Duties & Responsibilities: Responsibilities. - Qualifications & Requirements: Qualifications. - Preferred Experience: could be under Qualifications or maybe Skills? Could be separate "Preferred Experience" but not in list of allowed headings. Could fold into Qualifications as a subsection? But we must use only allowed headings. Could include "Qualifications" covering both required and preferred. Or we could add "Skills" heading for preferred experience? Probably better to keep Qualifications covering required and preferred. - Success Measures: maybe could be under Responsibilities? Not exactly. Could be omitted if not fitting headings. Could be part of Responsibilities? Might be considered metrics; but we have no heading for Success Measures. Could omit? But we must preserve ALL substantive information; cannot omit. We need to include that info somewhere. Could put under Responsibilities as additional bullet points? Or create a section "Performance Expectations"? Not allowed. Could put under Qualifications? Not ideal. Could create a section "Success Measures" but not in allowed list; instructions say use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but says "Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It implies we should use those headings when appropriate, but we could also use other headings? Probably safer to stick to those. However we need to include success measures; maybe we can incorporate them into Responsibilities as bullet points (they are about outcomes). Could be okay. - Pay: we have base salary range $144,000-$200,000. So we need a Pay section. - Benefits: we have benefits description; we need Benefits section. - Schedule: we have hybrid work model: in-person attendance at least three days per week. So we can put Schedule. - About Us: maybe not needed; but could be omitted as not required heading. Could be omitted? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." About Us is substantive. But we don't have a heading for About Us. Could we put it under About the role? That's about the role, not about us. Could we create a section "About Us"? Not in allowed list but maybe permissible? The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't say you cannot use other headings, but suggests those are typical. To be safe, we could include About Us as a paragraph without heading? But we need to preserve all info. Could embed About Us as a

after the role summary? Might be okay. - About The Team: also substantive. Could be included as paragraph. - Benefits details repeated; we need to include benefits info. We must remove boilerplate: cookie/navigation/legal/EEO etc. The text includes some boilerplate like "See how at www.gt.com/careers" etc. We should remove those lines. We need to output only HTML fragment, no /, no markdown fences. Let's extract content: Position Summary (About the role): "Grant Thornton GTech’s vision is centered around enabling scalable, secure, and repeatable data integration capabilities that support enterprise transformation, mergers and acquisitions, and modern analytics. The Data & Analytics function is responsible for designing and delivering governed data solutions that connect critical business and technology systems while enabling trusted reporting, archival, and analytics at scale. The Manager, Data & Analytics will be responsible for designing, building, testing, and supporting data pipelines within enterprise standards that enable the integration of systems from acquired companies, as well as data archival in Snowflake. This role will work closely with data architecture, enterprise architecture, application teams, security, infrastructure, implementation partners, and business stakeholders to deliver reliable, governed, and reusable data integration capabilities that support M&A integration, operational continuity, compliance, reporting, analytics, and long-term data asset management." Responsibilities (Essential Duties & Responsibilities): List each bullet as

. Let's capture them: - Design, build, test, and support enterprise data pipelines that enable integration of systems, applications, and data assets from acquired companies. - Implement data ingestion, transformation, validation, and archival patterns that align with enterprise data architecture, security, governance, and operational standards. - Support data archival solutions in Snowflake that enable acquired-company integration, historical reporting, data retention, compliance, and future analytics needs. - Work with data architecture and enterprise architecture teams to ensure pipeline designs follow approved architecture patterns, naming conventions, metadata practices, access controls, and integration standards. - Collaborate with M&A integration, application, infrastructure, security, and business teams to understand source-system requirements, data dependencies, integration timelines, archival needs, and target-state usage patterns. - Translate business, technical, and integration requirements into data pipeline designs, data mappings, transformation logic, quality rules, and deployment activities. - Develop and maintain scalable data engineering processes for batch, incremental, and event-driven data movement, where appropriate, across enterprise platforms and acquired-company systems. - Implement data quality checks, reconciliation routines, exception handling, monitoring, and operational controls to ensure pipelines are reliable, auditable, and production-ready. - Support data migration and archival activities by coordinating source extracts, transformation rules, target loading, validation outcomes, and issue resolution across internal and partner teams. - Work with analytics and reporting stakeholders to ensure integrated and archived data assets are structured to support downstream business intelligence, analytics, AI, and operational reporting use cases. - Coordinate with implementation vendors and technology teams to execute delivery activities, resolve blockers, validate deliverables, and ensure adherence to enterprise standards. - Create and maintain technical documentation, including data flow diagrams, pipeline specifications, source-to-target mappings, operational runbooks, metadata, and support handoff materials. - Support go-live readiness, cutover planning, data validation, post go-live hypercare, and transition of pipelines to steady-state data operations. - Identify opportunities to improve data engineering patterns, automation, reuse, performance, cost efficiency, data observability, and operational supportability. - Promote strong data engineering discipline, secure data handling, and consistent implementation practices within the Data & Analytics function. - Other duties as assigned. Qualifications & Requirements: List: - 6+ years of experience in data engineering, data integration, data architecture, analytics engineering, application integration, or related enterprise technology roles. - Demonstrated experience designing, developing, and supporting production data pipelines using modern ETL/ELT, orchestration, data warehousing, data lake, or cloud data platform technologies. - Hands-on experience with Snowflake, including data loading, transformation, schema design, performance considerations, access patterns, and operational support concepts. - Experience integrating data from multiple enterprise systems, acquired-company systems, SaaS platforms, ERP systems, operational applications, or legacy technology environments. - Working knowledge of source-to-target mapping, data transformation, data validation, reconciliation, data quality, metadata, lineage, and pipeline monitoring practices. - Understanding of enterprise data architecture standards, data security, access management, privacy, data retention, archival patterns, and governed data delivery practices. - Experience working with business stakeholders, application teams, architects, security, infrastructure, vendors, and delivery partners to translate requirements into implemented data solutions. - Ability to work in a fast-paced integration environment with multiple priorities, dependencies, delivery milestones, and business continuity requirements. - Strong problem-solving, communication, documentation, and stakeholder management skills, with the ability to explain technical concepts clearly to both technical and business audiences. - Bachelor’s degree in Information Systems, Computer Science, Engineering, Data Analytics, Business, or related field required; relevant cloud/data certifications preferred. Preferred Experience (could be included under Qualifications or Skills). Let's add as a subsection under Qualifications maybe as a separate

with heading? But we only allowed headings: Qualifications, Skills. Could treat Preferred Experience as Skills. Let's put under Skills heading. Skills (Preferred Experience): - Experience supporting merger, acquisition, divestiture, or acquired-company technology integration programs. - Experience with cloud data platforms and tools such as Snowflake, Azure Data Factory, Databricks, dbt, Informatica, Fivetran, Matillion, Airflow, or comparable data engineering technologies. - Experience with data archival, historical data retention, legacy system decommissioning, or compliance-driven data preservation initiatives. - Familiarity with analytics and reporting platforms such as Power BI, Tableau, Qlik, or comparable business intelligence tools. - Experience operating in a professional services, consulting, accounting, or complex global enterprise environment. - Experience contributing to reusable pipeline frameworks, engineering standards, data platform runbooks, and operational support models. Success Measures: we need to include. Could be placed under Responsibilities as additional bullet points? Or maybe under a heading "Performance Expectations"? Not allowed. Could incorporate as a paragraph under Responsibilities? Might be okay to add as a

after responsibilities list. But we must preserve all info. Let's add a

after responsibilities list titled maybe "Success Measures:" as plain text? But we cannot add heading not allowed? Could add a

with bold? Not heading. We'll just add a

with the success measures content. Success Measures bullet list: - Data pipelines for acquired-company system integration are delivered in alignment with enterprise standards, scope, timeline, and quality expectations. - Snowflake archival solutions are reliable, governed, validated, discoverable, and structured to support retention, reporting, analytics, and future reuse. - Source-to-target mappings, data quality checks, reconciliation outcomes, pipeline documentation, and operational handoffs are complete and supportable. - Integration and archival activities protect business continuity during cutover, go-live, and post go-live hypercare. - Data engineering patterns are reusable, secure, cost-aware, and aligned with enterprise data architecture and governance expectations. Pay: base salary range $144,000-$200,000. Also note placement discretion etc. We'll include that as

under Pay. Benefits: we have description: "We understand that your needs, responsibilities and experiences are different, and we think that’s a good thing. That’s why we support you with personalized and comprehensive benefits that recognize and empower all the identities, roles and aspirations that make you, well, you. For an overview of our benefit offerings, please visit: https://www.grantthornton.com/careers/rewards-and-benefits" plus details about interns/seasonal employees etc. We should include all that. Remove boilerplate like "See how at www.gt.com/careers". Keep the benefits description. Schedule: "Consistent with the firm's hybrid work model, this position will require in-person attendance at least three days per week, either at a GT office or client site." Also mention work-life integration options etc. We'll include that. About Us and About The Team: we need to preserve. Could add as paragraphs after Benefits maybe under a heading "About the Company"? Not allowed. Could just add as

without heading. That's okay. We must not repeat job title as heading. Already not. We must not include Job ID/requisition numbers. We must remove duplicated lines, cookie/navigation/legal/EEO etc. The text includes some like "At Grant Thornton, compensation decisions are dependent upon the facts and circumstances of each position and candidate." That's part of Pay description; we