Director, BI and Advance Analytics
Kestra Financial · Tempe, AZ · 1 mo ago
Business DevelopmentFull-time
We need to output HTML fragment with sections: h3 headings for sections present. Must not repeat job title. No Job ID. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Keep substantive info.
We need to parse the posting.
Key sections: About the role? Not explicit but we have description. Could use "About the role" heading for intro paragraph. Then "Responsibilities" for "What you’ll Do" and "Key Leadership Responsibilities". Could combine. "Requirements" or "Qualifications" for "What You Bring". "Skills" maybe for technical skills. "Benefits" for benefits listed. "Pay" not specified (just "Competitive pay and benefits" but no numbers; we should not create Pay section unless posting actually states them. It says "Competitive pay and benefits with a large employer". That's vague but still mentions pay. The rule: never create Pay/Schedule/Benefits sections unless the posting actually states them. It does state "Competitive pay and benefits". That's a statement about pay and benefits. So we could include a Benefits section (since benefits listed) and maybe Pay not needed as separate if not specific. Could combine Pay and Benefits? The instruction: Prefer a few substantive sections over many thin ones. So we could have a Benefits section that includes both pay and benefits statements. Or we could have a "Compensation and Benefits" heading but only allowed headings are listed: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We can use Benefits heading. Pay heading only if specific pay info; we have only "Competitive pay". Might be considered stating pay, but it's vague. Safer to not create Pay section, just include pay statement within Benefits? But Benefits heading is for benefits; we could include pay statement there as part of benefits. Or we could create a Benefits section and mention competitive pay there.
Schedule: not mentioned, so omit.
We need to remove duplicated lines, boilerplate like "Internal Application Policy", "Kestra Values", "Explore Life at Kestra", website links, LinkedIn, Apply Today, Disclosure, etc. Also remove "Lead with Purpose. Partner with Impact." maybe keep as part of intro? It's tagline but could be considered boilerplate? It's part of company description; maybe keep as part of About the role.
We need to preserve all substantive information: company description, role purpose, responsibilities, requirements, qualifications, skills, benefits.
Let's extract substantive paragraphs.
Intro: "Kestra Holdings offers industry-leading wealth management platforms for independent wealth management professionals nationwide. Kestra is dedicated to empowering independent financial professionals—including traditional and hybrid RIAs—to grow their businesses and deliver exceptional client service. We combine advanced business management technology with personalized consulting to provide unmatched scale, efficiency, and support. Our advisor-focused culture is built on innovation and advocacy, enabling advisors to offer comprehensive securities and investment advisory solutions to their clients. Lead with Purpose. Partner with Impact. Kestra Financial is seeking a strategic, business-focused leader to direct enterprise Business Intelligence, Advanced Analytics and AI. This role will lead the analytics strategy, Tableau Next capabilities, semantic modeling, executive and board reporting, AI-driven insights, and decision intelligence initiatives that power growth across the organization. The ideal candidate combines deep Wealth Management and Financial Services experience, executive presence, product analytics leadership and a proven record of building capabilities that influence measurable business outcomes. This leader will partner with business and technology executives to develop trusted enterprise data products and accelerate adoption of advanced analytics and AI."
That's a good intro for About the role.
Then "What you’ll Do:" with bullet points under Strategic Impact etc. We'll convert to
- .
Then "Key Leadership Responsibilities:" with subheadings: Analytics, AI & Business Value Strategy; Enterprise BI & Semantic Models; Wealth Management Analytics Leadership; Data Products & Cross-Functional Partnership; Team Leadership, Inherited Capability & Future Growth; Technical Leadership. Each has paragraphs. We'll treat as part of Responsibilities.
Then "What You Bring:" with bullet list of requirements. Then "Preferred Experience:" list. Then "Success Metrics & Outcomes:" list. Could be part of Requirements or Qualifications. We'll treat as Requirements.
Then "Benefits to support you:" list.
We need to avoid duplication: some points repeat.
We'll craft sections:
About the role
... (intro paragraph)
Responsibilities
- Strategic Impact: Shape decisions that drive advisor growth, client acquisition, operational efficiency and enterprise transformation.
- Innovation at Scale: Lead initiatives using Tableau Next, Databricks Lakehouse, governed semantic models, Generative AI and Decision Intelligence.
- Executive Visibility: Partner directly with executive, line-of-business and technology leaders to deliver measurable outcomes.
- Leadership Opportunity: Lead and develop BI, analytics engineering, analytics product and advanced analytics capabilities.
- Growth & Transformation: Modernize wealth management analytics and help establish an AI-enabled, data-driven organization.
- for any list of duties/requirements/benefits. So we can have a single list with each duty as
- . We'll include all duties from "What you’ll Do" and the detailed responsibilities. We need to ensure we don't lose detail. Let's extract each duty: From "What you’ll Do:" bullet points: - Strategic Impact: Shape decisions that drive advisor growth, client acquisition, operational efficiency and enterprise transformation. - Innovation at Scale: Lead initiatives using Tableau Next, Databricks Lakehouse, governed semantic models, Generative AI and Decision Intelligence. - Executive Visibility: Partner directly with executive, line-of-business and technology leaders to deliver measurable outcomes. - Leadership Opportunity: Lead and develop BI, analytics engineering, analytics product and advanced analytics capabilities. - Growth & Transformation: Modernize wealth management analytics and help establish an AI-enabled, data-driven organization. From "Key Leadership Responsibilities:" sections: Analytics, AI & Business Value Strategy: - Define and execute an enterprise Analytics and AI roadmap aligned to advisor growth, client experience, operational efficiency and business performance. - Prioritize predictive, prescriptive, Generative AI and Agentic AI use cases; establish value measures that quantify adoption and outcomes. - Partner with executives to embed decision intelligence and governed self-service analytics into business workflows. Enterprise BI & Semantic Models: - Own Tableau Next strategy and delivery of executive dashboards, board reporting, operational scorecards and self-service analytics. - Lead enterprise semantic models and reusable business metrics on the Databricks Lakehouse platform. - Deliver business-ready data products supporting advisor productivity, recruiting, retention, AUM/AUA, NNA, revenue, client engagement, compliance, practice management and operations. - Establish KPI governance, metric standardization and a trusted source of truth across business functions. Wealth Management Analytics Leadership: - Serve as a trusted advisor on advisor performance, recruiting effectiveness, retention, practice growth, asset flows, profitability, client acquisition, compliance and supervision. - Partner across Finance, Operations, Product, Compliance and Field Leadership to turn analytical findings into business action. Data Products & Cross-Functional Partnership: - The Director is accountable for analytics product strategy, business outcomes, user adoption and value realization. - Delivery will use an integrated operating model with shared roadmaps, backlogs, decision rights, quality gates and release criteria across the following teams: - Collaboration with Data Governance: Co-own KPI definitions, business glossary, data ownership and stewardship, quality rules, metadata, lineage, access controls and responsible AI requirements. Ensure each product has approved definitions, accountable owners and transparent controls. - Collaboration with Data Engineering, Data Products & Architecture: Translate product requirements into curated datasets, scalable pipelines and semantic-ready structures on Databricks. Jointly manage dependencies, nonfunctional requirements, performance, reliability, release readiness and production support. - Data Science, Security & Compliance: Operationalize advanced analytics and AI while embedding privacy, cybersecurity, model risk, supervision and regulatory requirements throughout design, deployment and monitoring. Team Leadership, Inherited Capability & Future Growth: - Assume leadership of Kestra’s existing BI and analytics delivery capability and assess current skills, capacity, role clarity and ways of working. - Create a cohesive operating model spanning BI development, analytics engineering, advanced analytics and analytics product management. - Mentor leaders and individual contributors; establish career paths, training, succession readiness and a culture of innovation, accountability and collaboration. - Develop a future capacity and talent plan aligned to demand and value realization. - Potential expansion may include BI developers, analytics engineers, analytics product managers, data scientists and AI/decision-intelligence specialists, subject to approved workforce plans. - Establish delivery governance that produces scalable, trusted and well-adopted analytics products. Technical Leadership: - Provide strategic oversight of Tableau Next, enterprise reporting architecture, semantic modeling and metric governance. - Leverage Databricks Lakehouse and Azure to enable scalable analytics and AI workloads. - Establish standards for data quality, metadata, governance, lineage, performance and reliability in partnership with Engineering and Architecture. - Drive responsible modernization through cloud-native and AI-enabled technologies. We'll convert each bullet to
- . Might be many but okay.
Now Requirements/Qualifications: "What You Bring:" list:
- 12+ years of experience in Business Intelligence, Analytics, Data or Decision Intelligence, including 5+ years leading enterprise analytics organizations.
- Deep expertise in Wealth Management, Financial Services, Broker-Dealer, RIA, Custodial, Asset Management or Investment Advisory businesses.
- Proven success building BI and Analytics capabilities and influencing senior executives through data-driven recommendations.
- Strong knowledge of wealth operations, advisor lifecycle, AUM/AUA, NNA, recruiting, retention, practice management, revenue and profitability analytics.
- Exceptional communication, executive presence, people leadership and cross-functional delivery skills.
Preferred Experience:
- Tableau Next/Tableau and Databricks Lakehouse; Azure; semantic layer, business glossary and KPI standardization; executive and board scorecards; Advanced Analytics, Generative AI, Agentic AI or Decision Intelligence programs; experience within a leading wealth management platform, custodian, broker-dealer, asset manager or large RIA; MBA or relevant advanced degree preferred.
Success Metrics & Outcomes:
- Business Impact: Measurable improvement in advisor productivity and contribution to AUM, AUA, NNA, revenue or operating outcomes.
- Analytics Transformation: Adoption of Tableau Next, standardized KPIs, governed semantic models, self-service analytics and reusable enterprise data products.
- AI & Innovation: Production deployment of high-value AI use cases with responsible controls, user adoption and quantified benefits.
- Leadership Excellence: A high-performing, scalable team with strong engagement, delivery discipline and succession readiness.
We could combine Requirements and Preferred Experience into a "Qualifications" section, and maybe "Skills" for technical skills. But we have limited headings; we can use Requirements for mandatory, Qualifications for preferred, Skills for technical. However we must not create sections with filler. We have content for each.
Let's decide:
Requirements
12+ years of experience in Business Intelligence, Analytics, Data or Decision Intelligence, including 5+ years leading enterprise analytics organizations.
Deep expertise in Wealth Management, Financial Services, Broker-Dealer, RIA, Custodial, Asset Management or Investment Advisory businesses.
Proven success building BI and Analytics capabilities and influencing senior executives through data-driven recommendations.
Strong knowledge of wealth operations, advisor lifecycle, AUM/AUA, NNA, recruiting, retention, practice management, revenue and profitability analytics.
Exceptional communication, executive presence, people leadership and cross-functional delivery skills.
Qualifications
Preferred experience includes:
- Tableau Next/Tableau and Databricks Lakehouse; Azure; semantic layer, business glossary and KPI standardization; executive and board scorecards; Advanced Analytics, Generative AI, Agentic AI or Decision Intelligence