Senior Technical Manager, Data, Analytics, and AI Solutions

Brunswick Boat Group•Fond du Lac, WI

4d•Hybrid

About The Position

The Senior Technical Manager, Data, Analytics, and AI Solutions is responsible for leading the design, planning, and delivery of data, analytics, reporting, ETL, and AI-enabled solutions. This role partners closely with business stakeholders, technology teams, data engineers, architects, analysts, and leadership to translate business needs into scalable technical solutions that support data-driven decision making. This position requires a strong blend of technical expertise, solution ownership, stakeholder engagement, project intake management, and team leadership. The ideal candidate possesses strong communication skills, deep understanding of data and analytics platforms, experience with ETL and reporting technologies, and the ability to build trusted partnerships across business and IT organizations. The role will serve as a technical leader and solution advisor, managing a team, helping shape data and analytics roadmaps, define phased implementation plans, manage demand intake, and ensure that solutions are aligned to enterprise architecture, business value, and long-term platform strategy.

Requirements

Bachelor’s degree in Information Systems, Computer Science, Data Analytics, Engineering, Business, or a related field.
7+ years of experience in data, analytics, business intelligence, ETL, reporting, solution delivery, or related technology roles.
3+ years of people leadership or technical team leadership experience.
Strong experience conducting requirements gathering and translating business needs into technical requirements.
Experience developing roadmaps, phased implementation plans, and technical delivery strategies.
Strong understanding of data integration, ETL, data warehousing, data modeling, reporting, dashboards, and analytics platforms.
Experience working with business stakeholders and technical teams in a cross-functional environment.
Proven ability to manage project intake, prioritize demand, and align work to business value and technical feasibility.
Strong communication skills with the ability to explain technical concepts to non-technical audiences.
Experience supporting enterprise-scale data and analytics solutions.

Nice To Haves

Experience with Oracle Analytics technologies, including Oracle Analytics Cloud, OBIEE, Oracle BI Applications, Oracle data warehouses, or Oracle semantic/reporting layers.
Experience with Azure technologies such as Azure Data Factory, Azure Synapse, Azure Data Lake, Azure Databricks, Azure SQL, Azure AI Services, Microsoft Fabric, and Power BI.
Experience with ETL and data integration tools such as Informatica, Microsoft Fabric/Synapse/Data Factory, and Alteryx.
Experience with reporting, BI, or ETL tool consolidation initiatives.
Experience modernizing legacy reporting platforms and migrating to cloud-based analytics ecosystems.
Experience with data governance, metadata management, data quality, master data, and semantic layer design.
Certifications in Azure, Power BI, Microsoft Fabric, Oracle, Agile, Scrum, PMP, CBAP, or related disciplines are a plus.

Responsibilities

Act as a trusted technical partner to business stakeholders and technology leaders.
Partner with business teams to understand operational challenges, data needs, reporting gaps, and analytics opportunities.
Communicate complex technical concepts in a clear, business-friendly manner.
Facilitate alignment between business priorities and technical delivery plans.
Build strong partnerships across business functions, IT, enterprise architecture, data engineering, analytics, AI, and project delivery teams.
Support change management, adoption, training, and value realization for delivered solutions.
Lead technical planning, design, and delivery of data, analytics, reporting, ETL, and AI-related solutions.
Partner with architects, engineers, analysts, and business teams to define scalable solution approaches.
Translate business objectives into technical requirements, solution designs, data flows, integration patterns, and implementation plans.
Provide technical oversight across data pipelines, reporting environments, semantic layers, dashboards, data models, and analytics platforms.
Ensure solutions are scalable, secure, supportable, and aligned with enterprise data and technology standards.
Evaluate technical tradeoffs, dependencies, risks, and architecture considerations for data and analytics initiatives.
Lead workshops, stakeholder interviews, and discovery sessions to identify business needs and opportunities.
Conduct requirements gathering sessions with business stakeholders, subject matter experts, and technical teams.
Elicit and document business, functional, technical, data, reporting, and integration requirements.
Translate business requests into detailed user stories, technical specifications, data mapping documents, process flows, and acceptance criteria.
Validate requirements with stakeholders and ensure requirements are clear, complete, and actionable for delivery teams.
Bridge communication between business users and technical teams to ensure shared understanding of needs, constraints, and solution design.
Develop and maintain data, analytics, reporting, ETL, and AI solution roadmaps.
Create phased implementation plans that balance business value, technical complexity, platform readiness, resource availability, and dependencies.
Sequence initiatives across short-term tactical needs and long-term strategic modernization efforts.
Support technology rationalization, platform modernization, cloud migration, and analytics transformation planning.
Partner with business and IT leadership to prioritize investments and define delivery milestones.
Communicate roadmap progress, risks, dependencies, and decision points to leadership and stakeholders.
Provide technical leadership across ETL, data integration, business intelligence, reporting, and analytics platforms.
Bring experience with ETL and data integration tools such as Microsoft Fabric/Synapse/Data Factory, Informatica, and Alteryx.
Support design and delivery of data pipelines, data models, transformation logic, and reporting datasets.
Understand enterprise reporting and analytics environments, including dashboarding, semantic models, data marts, data warehouses, and self-service analytics.
Provide technical guidance for Oracle Analytics environments, including Oracle Analytics Cloud, OBIEE, Oracle data models, and related reporting ecosystems.
Partner with technical teams to modernize legacy reporting and data integration environments into cloud-based analytics platforms.
Support cloud data architecture, data movement, data transformation, data storage, security, and performance considerations.
Help evaluate where AI, machine learning, automation, and natural language analytics can improve business processes and insights.
Ensure data solutions align with enterprise security, governance, privacy, and compliance requirements.
Lead or support ETL, reporting, and analytics tool consolidation initiatives.
Assess duplicate tools, overlapping capabilities, redundant reports, fragmented data sources, and inconsistent reporting processes.
Develop recommendations for rationalizing reporting platforms, ETL tools, dashboards, and analytics assets.
Partner with business and technical teams to migrate reports, retire legacy solutions, and standardize on strategic platforms.
Support modernization efforts from legacy BI platforms to modern cloud-based data and analytics solutions.
Help define enterprise standards for reporting, data integration, analytics delivery, and self-service enablement.
Manage the intake process for data, analytics, reporting, AI, and technology requests.
Evaluate incoming requests for business value, technical complexity, strategic alignment, dependencies, resource needs, and platform fit.
Facilitate intake review sessions, prioritization discussions, and roadmap alignment meetings.
Maintain visibility into demand pipeline, project backlog, delivery status, and resource capacity.
Ensure incoming requests are properly scoped, documented, prioritized, and transitioned to delivery teams.
Establish consistent processes, templates, and governance practices for intake and requirements management.
Lead, coach, and develop a team of technical, business, and data analysts.
Set team goals, delivery expectations, development plans, and performance standards.
Provide guidance on requirements gathering, technical analysis, solution design, stakeholder management, and delivery best practices.
Manage team workload, resource allocation, project assignments, and capacity planning.
Build a high-performing team culture focused on technical excellence, accountability, collaboration, and continuous improvement.
Mentor team members on data platforms, analytics tools, AI concepts, cloud technologies, and enterprise delivery practices.
Establish reusable standards, documentation templates, solution patterns, and delivery methods.