We are looking for a Data Analytics Manager 6 Insights to lead a team responsible for turning complex data into clear, actionable recommendations for senior leaders, internal business partners, and external client audiences. This is a hands-on leadership role for someone who can guide analysts, work directly in the data, shape ambiguous business questions, and deliver trusted insights that influence decisions.

You will lead a small team of analysts whose work supports business performance, client relationships, operational strategy, and executive-level decision-making. You will balance people leadership, analytics delivery, stakeholder prioritization, and the continued modernization of the team
9s reporting and insight capabilities.

• Lead analytical projects end to end, including problem framing, project planning, data discovery, analysis, validation, insight development, and recommendation delivery.
• Translate open-ended business questions from internal leaders and client-facing teams into a clear analytical approach, data plan, and measurable answer.
• Use data to identify trends, root causes, risks, opportunities, and performance drivers across business operations, client portfolios, and strategic priorities.
• Present complex findings to senior leaders and external client audiences in plain language, with a clear
  5so what,
  6 recommended actions, and business implications.
• Own the quality of what leaves the team, including accuracy, reconciliation, reproducibility, documentation, and consistency of every number shared with clients or executives.

• Lead, coach, and develop a team of analysts, setting clear goals, expectations, priorities, and standards for quality and delivery.
• Provide regular feedback, conduct performance and development conversations, and help analysts grow their technical depth, business judgment, communication, and stakeholder impact.
• Review analytical approaches, SQL, data models, dashboards, and recommendations to raise the level of the work, not just check completion.
• Manage workload and capacity across competing priorities, assigning work based on business value, urgency, skills, and development opportunities.
• Support hiring, onboarding, retention, and talent development across the broader Data Analytics organization.

• Drive standardization, automation, and reuse of recurring reporting, dashboards, semantic models, datasets, and analytical assets so the team spends more time on insight and less time on manual assembly.
• Advance data modeling, metric definition, documentation, quality controls, and governance best practices across Power BI, Microsoft Fabric, and related analytics environments.
• Partner with Data Engineering, IT, Security, business teams, and other analytics groups to ensure solutions are scalable, secure, well-documented, and production-ready.
• Establish practical standards for data privacy, access controls, testing, release readiness, issue resolution, and responsible use of AI-assisted analytics tools.
• Identify opportunities to modernize legacy reports, reduce duplication, improve performance, and increase adoption of trusted, governed self-service analytics.

• Own intake and prioritization for the team
  9s work, making tradeoffs visible and aligning requests to business value, urgency, capacity, and leadership priorities.
• Proactively engage internal and client-facing teams to identify analytical needs before they arrive as requests and shape them into high-value use cases.
• Stay current with trends in insurance, protection and support services, analytics, BI technology, Microsoft Fabric, and responsible AI adoption, bringing forward what is worth testing or scaling.

• You understand the team, the business partners, the reporting portfolio, the data estate, and the highest-value decision points the team supports.
• You have established a clear intake and prioritization rhythm, and stakeholders understand how decisions are made.
• You are reviewing critical outputs for quality, clarity, and business relevance before they reach senior leaders or clients.

• The quality and consistency of the team
  9s work has visibly improved through stronger review habits, reproducible analysis, better documentation, and clearer storytelling.
• You have identified recurring reporting and manual processes that should be automated, consolidated, retired, or moved into governed self-service.
• You are personally presenting insights and recommendations to senior leaders or client audiences and helping the team do the same with confidence.

• Measurable time has shifted from manual reporting assembly into analysis, advisory work, and higher-value decision support.
• The team
  9s Power BI and Fabric assets are more standardized, governed, better documented, and easier for stakeholders to trust and use.
• At least one analyst has grown into materially more complex work through your coaching and development.
• The team is engaged earlier in business decisions, helping shape the question rather than only responding after the request is fully defined.

• Bachelor
  9s degree in Business Analytics, Statistics, Economics, Applied Mathematics, Computer Science, Information Management, or a related quantitative field; equivalent work experience may be considered.
• 7+ years of experience in analytics, business intelligence, reporting, data management, research, or a related data-focused field.
• 2+ years of experience formally leading, supervising, or managing analysts, or equivalent experience leading analytical work through others.
• Demonstrated ability to translate complex analysis into recommendations that influence business decisions.
• Experience leading analytical projects from intake and scoping through delivery, presentation, adoption, and follow-up.
• Experience managing competing stakeholder priorities, team capacity, timelines, quality standards, and delivery expectations.

• Advanced SQL skills, including complex joins, window functions, CTEs, performance tuning, data validation, and the ability to work directly with enterprise data warehouses.
• Strong Power BI experience, including data modeling, star schema design, DAX, semantic model development, row-level security, report performance tuning, and governed self-service analytics.
• Working knowledge of Microsoft Fabric, including Lakehouse/Warehouse concepts, Direct Lake, pipelines, notebooks, or comparable experience with modern cloud/lakehouse analytics platforms.
• Strong understanding of data quality, data governance, metric consistency, documentation, access controls, and reporting reliability.
• Advanced Excel skills and comfort using modern analytics, automation, and AI-assisted tools to improve productivity and documentation.

• Excellent written, verbal, and interpersonal communication skills, with the ability to communicate effectively with technical teams, non-technical stakeholders, senior leaders, and client audiences.
• Strong data storytelling skills, including the ability to simplify complex or ambiguous findings into clear messages, business implications, and recommended actions.
• Executive presence and confidence presenting to, advising, and being challenged by senior leaders and external stakeholders.
• Ability to build trust, influence decisions, manage tradeoffs, and keep stakeholders aligned when priorities shift.

• Master
  9s degree in business, analytics, statistics, applied mathematics, operations research, economics, engineering, computer science, or a related quantitative field.
• Experience in insurance, telecommunications, retail, warranty, service operations, client operations, or other data-rich operational environments.
• Experience with Databricks, Apache Spark, Azure, Python, R, predictive modeling, time series forecasting, segmentation, cluster analysis, retention analysis, or exploratory analytics.
• Experience modernizing legacy reporting, consolidating dashboards, defining KPI frameworks, improving semantic models, and increasing adoption of trusted analytics products.
• Experience with Agile delivery, product ownership, portfolio prioritization, user acceptance testing, release management, or change management for analytics solutions.
• Hands-on use of AI-assisted coding, documentation, or analytics tools to accelerate analysis, automate recurring work, or build internal tooling responsibly.
• A track record of developing talent, leading through influence, and creating a culture of curiosity, accountability, inclusion, and continuous improvement.