Customer Solutions Architect Manager

4 trends for activating data with context. Takeaways from Slalom's Insurance Leaders Lunch at the Databricks Data & AI Summit. Matt Edwards Senior Director Published: Aug 17, 2026 Tl;dr. * Slalom, in partnership with Atlan, Fivetran and Databricks, hosted an Insurance Leaders Lunch and panel discussion during the 2026 Databricks Data & AI Summit. Insurance, data, and AI leaders discussed, How do insurers move from having data to activating it to driving smarter decision-making? * The session opened by framing the challenges around four interconnected trends reshaping the industry. Those trends are human-AI collaboration, data fluidity and intelligent systems, ecosystem modularization, and self-directed systems. * The throughline connecting all four trends? Context. Context = shared definitions, data lineage, quality, regulatory constraints, and the "why" behind a recommendation. - Without context, even the most sophisticated AI systems fall flat in insurance operations. Thank you to its community of panelists: * Tom Linton, Head of World Wide Sales Engineering, Atlan * Marcela Granados Lavoie, Principal, Global Head of Insurance, Databricks * Zach Taher Vice President, Data Engineering, Northwestern Mutual * Dylan Austin, Vice President, MLOps Engineering, PURE Insurance What one foundational capability must insurers get right in the next two years? The panel's answer was remarkably aligned: All panelists agreed that data quality and governance, paired with intentional information architecture is the most important foundational capability for insurance industry technology and LOB leaders. You cannot build trustworthy AI on untrustworthy data. Invest in the foundations you need for clean, well-defined, well-governed data with rich context attached. What are the larger set of challenges reshaping the insurance industry right now? Trend 1: Human+AI collaboration. Two ideas came forward around human+AI collaboration: AI for augmentation, and trust through transparency. AI for augmentation The panel was clear: underwriters, claims professionals, and agents aren't replaceable. They're essential. At the same time, insurance professionals' impact can - and must - be augmented with AI. AI makes it possible for insurance pros to complete their goals, deliver work that's more consistent, and make better informed decisions. Trust through transparency The discussion highlighted how technology platforms can surface data lineage and business definitions directly within AI-powered workflows. Practitioners can examine the "why" behind a recommendation, not just see and nod along to the output. When end users actively shape AI, trust compounds over time. Trend 2. Data fluidity and intelligent systems. The insurance industry has plenty of data. Data shortage hasn't been a problem in a long time. The problem is data accessibility and trust problem. That problem becomes more challenging with the evolution to more modular ecosystems. Data that is discoverable, well-governed, and that can flow to the right system - at the right time - with the right context attached - is critical for developing insights and driving transformation. Modern platforms like Databricks and Atlan are enabling insurers to connect disparate data sources with the appropriate context to build richer, AI-ready data products. Insurance organizations are still working to address siloed systems that continue to create blind spots that directly impact underwriting accuracy, claims outcomes, and fraud detection. What's the practical starting point? The panel agreed that leaders must invest in discoverability and metadata management before trying to build intelligent systems on top of data you can't find or trust. Trend 3. Ecosystem modularization. Move over monolithic insurance platforms. Here come composable, modular architectures. The panelist conversation reinforced that data solutions are not separate from modernization strategy. They're foundational to making modular ecosystems work and unlocking value across the organization. Rather than rebuilding capabilities system by system, modular ecosystems allow insurers to expose reusable data and analytics building blocks across the enterprise and with partners. This shift also makes it far easier to integrate best-in-class solutions without ripping and replacing core systems like a data catalog, a feature store, or a fraud detection model. Trend 4. Self-directed systems. * Automated underwriting for simple risks * Real-time fraud blocking * Intelligent claims triage These solutions currently exist, but AI is making them more intelligent, adaptable and accessible across lines of business. As these self-directed systems become table stakes, guardrails must be audited to ensure proper decisioning and transparency. "Policy as code," continuous monitoring, explainability frameworks, and clear human escalation paths aren't bureaucratic overhead. Full stop. They are essential in making automation sustainable and auditable. Platforms like Atlan and Databricks are valuable in ensuring self-directed systems perform as intended so they don't drive adverse business outcomes or fail auditability and regulatory requirements. Thank you again to its generous panelists and its community of practitioners at the Data & AI Summit. It was great to be in conversation! | SET AI IN MOTION | | Move AI from experimentation into everyday operations. * Adaptable foundations * Human+AI workflows * Measurable outcomes * $8B+ in customer value * 3x average ROI |

Fivetran selected by Oakbrook Finance to support real-time lending decisions and AI-ready data operations. Fivetran, the data foundation for AI, today announced that specialist UK consumer lender Oakbrook Finance has selected the company to centralise and govern data across its analytics estate. The deployment supports customer insight, product development, marketing effectiveness and machine learning workflows, while saving Oakbrook's data engineering team approximately three months of build time. Founded in 2011, Oakbrook is a specialist consumer lender serving near-prime and non-prime borrowers across the UK who are typically overlooked by mainstream banks. The business has lent more than £1.5 billion to UK customers and currently serves around 140,000 active borrowers. A significant share of applications comes through price comparison platforms, where Oakbrook typically has less than 10 seconds to ingest data, run its models, and return an offer. "Our data engineering team is lean and deliberately focused. Before Fivetran, a meaningful chunk of their time was spent maintaining pipelines rather than building things that move the business forward," said Ed Ball, Head of Data and Security at Oakbrook. "Fivetran has let us connect data sources we wouldn't have reached otherwise, which has materially expanded what we can analyse and model, from customer behaviour through to how our products perform in the market. That's directly fed into work like the launch of OakbrookOne, our debt consolidation product." To meet these requirements without increasing operational overhead, Oakbrook adopted an automated approach to data integration. Fivetran enables the company to centralise and govern data from multiple sources, supporting an open data infrastructure model in which data remains accessible, consistent, and under Oakbrook's control. "Financial services organisations are under pressure to move faster while maintaining strict governance and control over their data," said Alex Cresswell, Regional Vice President, Northern Europe, Middle East and Africa (NEMEA) at Fivetran. "An open data infrastructure allows them to do both, by ensuring data is accessible, governed, and usable across systems without adding operational complexity." Fivetran now ingests around 5 million rows of data for Oakbrook each month, creating a consistent, governed data layer across the business. This supports improved customer insight, application development, and marketing effectiveness, including the launch of new products such as OakbrookOne, a debt consolidation loan product that has so far enabled more than £50 million in consolidation lending, with customers saving an average of £110 a month and over 40 percent receiving same-day settlement of their existing debts.

Fivetran awarded 2026 Databricks ISV Customer Impact Partner of the Year at Data + AI Summit. Award recognizes Fivetran's role in helping enterprises accelerate AI adoption and deliver measurable business outcomes on the Databricks platform OAKLAND, Calif.-(BUSINESS WIRE)-Fivetran, the data foundation for AI, today announced that it has been named the 2026 Databricks ISV Customer Impact Partner of the Year. Presented at the annual Databricks Partner Awards during Data + AI Summit, the award recognizes Fivetran's success in helping joint customers accelerate analytics and AI initiatives through trusted, automated access to governed enterprise data. Together with Databricks, Fivetran is helping enterprises create the reliable data foundations and enterprise context needed to power analytics, AI applications, and agentic workflows. Share The recognition follows a year of strong momentum between Fivetran and Databricks, marked by substantial growth in their shared customer base and continued expansion of joint customer adoption worldwide. "Organizations are moving quickly from AI experimentation to production, and success depends on having access to trusted, governed data," said George Fraser, CEO and Co-founder at Fivetran + dbt Labs. "Together with Databricks, we're helping enterprises create the reliable data foundations and enterprise context needed to power analytics, AI applications, and agentic workflows. This award reflects the impact our teams and customers are achieving together." "As the race to productionize AI accelerates, customers consistently ask us how they can better manage their data in order to build AI apps and agents that make a real impact on their business," said Stephen Orban, SVP, Product Ecosystem & Partnerships at Databricks. "As a key Databricks partner, Fivetran helps our joint customers do exactly that. We're proud to recognize them as 2026 Databricks ISV Partner of the Year." Throughout the past year, Fivetran has deepened its collaboration with Databricks across product innovation, customer success, and go-to-market initiatives. The partnership enables organizations to centralize and operationalize data from hundreds of business-critical applications and databases within the Databricks platform, accelerating time-to-value for analytics, AI applications, and agents. The partnership has helped customers achieve measurable results, including Inova Health, which compressed a 4-year modernization roadmap into six months, reduced data movement costs by up to 8x, and eliminated a backlog of more than 500 requests while building a foundation for AI applications. Additionally, Superhuman accelerated data integration timelines from months to days, enabling faster reporting, AI-ready workflows, and improved customer outcomes. The integration with Databricks extends across the platform, including Unity Catalog, Lakehouse, Lakebase, Marketplace, Genie, and Agent Bricks. By delivering trusted, real-time data into Databricks, Fivetran helps organizations strengthen governance, improve operational efficiency, and accelerate adoption of AI-powered applications and analytics. Together, Fivetran and Databricks are helping organizations build and scale analytics, AI applications, and agents on trusted, governed enterprise data. About Fivetran + dbt Labs Fivetran + dbt Labs deliver the data infrastructure layer that makes agents trustworthy - from the moment data moves, through every transformation, to the context an agent reasons from. The Fivetran platform moves, manages, and transforms data from every system a business runs on into a secure, reliable foundation engineered to evolve, with the flexibility to work across clouds, engines, and tools. With Fivetran, analytics, operations, and AI run on data you trust and control. Thousands of organizations worldwide, including OpenAI, LVMH, Pfizer, and Verizon, rely on Fivetran to turn data into a competitive advantage. Since 2016, dbt Labs has been on a mission to help data practitioners create and disseminate organizational knowledge. dbt is the standard for AI-ready structured data. Powered by the dbt Fusion engine, it unlocks the performance, context, and trust that organizations need to scale analytics in the era of AI. Globally, more than 100,000 data teams use dbt, including those at Siemens, Roche and Condé Nast. More News From Fivetran OAKLAND, Calif.-( BUSINESS WIRE )-Fivetran, the data foundation for AI, today announced the completion of its merger with dbt Labs, the creator of dbt and the leader in standards for AI-ready structured data. Initially operating as Fivetran + dbt Labs, the all-stock transaction, originally announced on October 13, 2025, brings together two category-defining platforms to advance a new era of trusted, Open Data Infrastructure for AI at scale. George Fraser will continue serving as CEO, and Trista... OAKLAND, Calif.-( BUSINESS WIRE )-Fivetran, the data foundation for AI, today announced plans to become steward of the Great Expectations open source community and GX Core project, supporting the continued development of one of the industry's most widely used open source data quality frameworks. Under the planned transition, GX Core will continue as an open source, community-driven project. Fivetran intends to support ongoing project maintenance, ecosystem integrations, and community engagement... OAKLAND, Calif.-( BUSINESS WIRE )-Fivetran, the data foundation for AI, today released "The 2026 agentic AI readiness index," a global benchmark measuring how prepared enterprise data environments are to support agentic AI workloads/initiatives in production. The findings show that only 15% of organizations are fully prepared to support agentic AI in production, even as nearly 60% report investing millions to tens of millions in the technology. Based on a survey of 400 data professionals across... Fivetran. Release Versions