Manager, Data & Analytics

Grant Thornton; Southfield (MI); On-site; USD 120,000 - 180,000; Full time

Job summary

Grant Thornton is seeking a Data & Analytics Manager in Michigan to lead data pipeline design, build, and governance aligned with enterprise standards. The role focuses on integrating systems from acquired companies, data archival in Snowflake, and delivering trusted reporting and analytics at scale.

You will collaborate with data architecture, enterprise teams, security, and business stakeholders to enable compliant, scalable data solutions supporting M&A integration and long-term data asset

Qualifications

• 6+ years in data engineering, integration, or analytics roles.
• Experience designing and supporting production data pipelines.
• Hands-on Snowflake data loading, transformation, and design.
• Experience integrating data across enterprise systems and SaaS.
• Knowledge of metadata, lineage, and data quality practices.
• Understanding of governance, security, and archiving patterns.
• Ability to translate requirements into implemented data solutions.
• Strong communication and stakeholder-management skills.
• Bachelor’s degree and relevant cloud/data certifications preferred.

Responsibilities

• Design, build, test, and support enterprise data pipelines.
• Implement ingestion, transformation, and archival patterns.
• Support Snowflake archival for acquired-company data.
• Ensure pipeline designs follow architecture standards and governance.
• Collaborate with M&A, application, security, and infra teams.
• Translate requirements into mappings, logic, and deployment steps.
• Develop scalable data engineering processes for batch, incremental, and event-driven movement.
• Implement data quality checks, monitoring, and operational controls.
• Coordinate data migration and archival across teams and partners.
• Support BI/analytics use cases with integrated data assets.
• Create technical documentation and runbooks.

Skills

Data engineering

Data integration

ETL/ELT

Data warehousing

Snowflake

Cloud platforms

Stakeholder management

Documentation

Problem solving

Communication

Education

Bachelor's degree in Information Systems

Computer Science

Engineering

Data Analytics

Cloud certifications preferred

Tools

Snowflake

Azure Data Factory

Databricks

dbt

Informatica

Fivetran

Airflow

Power BI

Tableau

Job description

Grant Thornton is seeking a Data & Analytics Manager to join the team. Approved office locations can be found below.

Manager, Data & Analytics – Position Summary:

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.

Essential Duties & Responsibilities:

• 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

• 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

• 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.