← fivetran / Senior Product Manager, Enterprise Platform
candidate_questions / art_bKxnwwW0sdE
role
model
anthropic/claude-sonnet-4.6
created
2026-08-19T16:27
Interviewer
Casey Karst is a Principal Product Manager at Fivetran (since June 2025), focused on making it easier for customers to develop and deploy Managed Data Lakehouses. Before Fivetran, Casey spent 1.5 years as Director of PM at Dremio driving their Catalog and Engine products — including Apache Iceberg, Apache Polaris, and dbt integration — and prior to that was the founding PM at RelationalAI focused on customer onboarding, security, and scale-out computation. Casey also spent nearly 8 years at Microsoft on Azure SQL Data Warehouse and PolyBase, giving him deep roots in data infrastructure and cloud data loading. His background at Splunk — specifically leading Splunk Data Manager to automate data ingestion from Azure, M365, AWS, and GCP — is a direct parallel to Felix's own Splunk tenure on Search Orchestration and Kaiser's Splunk Logging-as-a-Service work. Casey's engineering foundation (Olin College, mechanical engineering) and his pattern of joining companies at inflection points (founding PM at RelationalAI, early at Dremio) suggest he values technical depth and first-principles thinking. Expect the conversation to lean into data infrastructure, lakehouse architecture, enterprise platform strategy, and the Fivetran-dbt Labs integration.
Questions to ask them (20)
| category | question | why |
|---|---|---|
| interviewer_experience | You were the founding PM at RelationalAI and came in early at Dremio — and now you're at Fivetran during what sounds like a significant inflection point with the dbt Labs integration. What draws you to these early or pivotal moments at companies, and what's been different about this particular chapter at Fivetran? | Opens a genuine conversation about Casey's career philosophy, signals you've read his trajectory carefully, and surfaces what he finds energizing about the current moment — which tells you a lot about the opportunity. |
| interviewer_experience | At Dremio you were driving both Catalog and Engine simultaneously — Apache Iceberg, Polaris, query planning, dbt integration. That's a wide surface area. How did you think about prioritization across those workstreams, and are there lessons from that experience you're applying to how you structure product work at Fivetran now? | Demonstrates you understand the technical breadth of his Dremio work and invites him to share frameworks he actually uses — useful intel for how this team operates. |
| interviewer_experience | Your time at Microsoft on PolyBase and Azure SQL Data Warehouse gave you a long view on how enterprise data loading has evolved. From where you sit now at Fivetran, what feels most different about the current generation of data infrastructure challenges compared to what you were solving in the Azure era? | Leverages his deepest technical roots to spark a substantive conversation and signals you're thinking about the historical arc of the space, not just the current moment. |
| role_team_dynamics | The role spans enterprise security and governance, workspace configuration, and observability tooling — that's a meaningful surface area. How is that scope currently divided across PMs on the Enterprise Platform team, and where would a new senior PM be expected to take the most ownership soonest? | Gets concrete about team structure and where the real leverage is, so you can assess fit and set realistic expectations. |
| role_team_dynamics | What does success look like at 30, 60, and 90 days in this role — and how much of that is about shipping versus listening and orienting? | Classic but essential — understanding the ramp expectation tells you whether the team needs a builder or a strategist first, and how much runway you have to learn the domain. |
| role_team_dynamics | What's the most pressing unsolved problem on the Enterprise Platform roadmap right now — the thing that keeps the team up at night or that customers are loudest about? | Surfaces the real pain points rather than the polished narrative, and gives you a chance to react with relevant experience. |
| role_team_dynamics | How does the Enterprise Platform team interface with the connector and pipeline teams day-to-day? Is the relationship more of an internal platform provider, a peer collaborator, or something else? | Understanding the internal customer dynamic is critical for a platform PM — this tells you how much influence you'll have and how decisions get made. |
| technical_environment | The JD mentions enterprise-grade security and governance — SSO, RBAC, audit logging. How mature is Fivetran's current implementation of those capabilities, and where are the biggest gaps that this role would be expected to close? | Gets specific about the technical state of the product and where the real work is, rather than accepting a polished surface-level answer. |
| technical_environment | Given your work at Dremio on Apache Iceberg and Polaris, and Fivetran's positioning around the Managed Data Lakehouse — how much does the Enterprise Platform PM need to engage with open table format standards and lakehouse architecture decisions, versus focusing purely on the platform layer above them? | Connects his specific expertise to the role scope and helps you understand how deep the technical engagement goes for this PM seat. |
| technical_environment | How does the team currently handle observability and telemetry for the platform itself — are PMs expected to get into the data directly, or is there a data/analytics function that mediates that? | Directly relevant to your background doing SQL/BigQuery analysis at Intuit — helps you understand how much self-serve data access you'd have and whether your analytical instincts would be well-utilized. |
| culture_working_style | You've been at companies ranging from a startup like RelationalAI to Microsoft's scale. How would you characterize Fivetran's operating style right now — especially as the dbt Labs integration is underway? Does it feel more like a scaling startup or an enterprise software company in how decisions get made? | The merger creates genuine cultural uncertainty — this question surfaces the real operating environment without being naive about the complexity. |
| culture_working_style | When a PM and an engineering lead disagree on scope or approach for a platform feature, how does that typically get resolved here? Is there a strong culture of data-driven escalation, or does it come down to relationship and influence? | Tells you how much organizational capital matters versus analytical rigor — important for calibrating how to operate effectively. |
| culture_working_style | How much autonomy does a Senior PM on this team have to define their own roadmap versus inheriting a largely pre-set direction from leadership? | Critical for understanding whether this is a role where you'd be building strategy or executing someone else's vision. |
| growth_development | You've moved from Senior PM at Microsoft to Principal at multiple companies to Director at Dremio and back to Principal at Fivetran — it seems like you've optimized for impact and domain fit over title trajectory. For a Senior PM joining this team, what's the realistic growth path, and how does Fivetran think about promotion versus lateral growth? | Frames the question around his actual career choices (non-linear, impact-driven) rather than assuming a standard ladder, which is more authentic and likely to get a candid answer. |
| growth_development | Given that this role sits at the intersection of data infrastructure, enterprise security, and platform extensibility — are there opportunities to develop deeper expertise in areas like the lakehouse architecture or open standards work, or does the PM role stay more at the product layer? | Signals intellectual curiosity about the technical domain and helps you assess whether the role would stretch you in the right directions. |
| strategy_vision | With the Fivetran and dbt Labs integration underway, how does the Enterprise Platform team's roadmap change — or does it? Are there new platform capabilities that only make sense in the combined company context? | The merger is the biggest strategic variable right now — understanding how it reshapes the platform roadmap is essential for evaluating the role's trajectory. |
| strategy_vision | The JD mentions keeping an eye toward AI-first opportunities. What does that concretely mean for the Enterprise Platform team — are there specific AI-native features on the horizon, or is it more about ensuring the platform is a reliable substrate for customers building AI applications? | Separates genuine AI strategy from marketing language and helps you understand where you'd actually be investing time. |
| strategy_vision | Where do you see the biggest competitive pressure on Fivetran's enterprise platform capabilities over the next 18–24 months — is it from hyperscalers building native data movement, from open-source tooling, or from somewhere else? | A strategic question that invites Casey to share his honest competitive read and signals you're thinking about the market, not just the product backlog. |
| shared_context | We overlapped at Splunk — you were building Splunk Data Manager to automate cloud data ingestion from AWS, Azure, and GCP, and I was on the Search Orchestration side owning the Search Service and SPL. I'm curious how you think about the lessons from that era of cloud-native data pipelines and what carried forward into your work at Dremio and now Fivetran. | Direct shared context — both worked at Splunk during overlapping periods on adjacent problems. This is a genuine rapport-builder and a substantive technical conversation starter. |
| shared_context | At Intuit I spent a lot of time on developer-facing platform infrastructure — SDKs, DevPortal, self-service onboarding — and one of the hardest problems was balancing the needs of internal platform consumers with the velocity demands of product teams. Given your experience as the founding PM at RelationalAI where you owned onboarding and security simultaneously, how did you navigate that tension, and do you see a similar dynamic on the Enterprise Platform team here? | Connects your Intuit platform experience to his RelationalAI founding PM work — establishes peer credibility and surfaces a real operational challenge you'd both recognize. |
Conversation starters
- I saw you were at Splunk around the same time I was — you were building Data Manager to automate cloud log ingestion and I was on the Search Orchestration side. Small world. I'd love to hear how that experience shaped how you think about data pipeline automation now.
- Your path from PolyBase at Microsoft to Iceberg and Polaris at Dremio to Managed Data Lakehouses at Fivetran feels like you've been tracking the evolution of the data warehouse-to-lakehouse shift from the inside for over a decade. That's a pretty rare vantage point.
- I noticed you were the founding PM at RelationalAI — I've always been curious what it's like to be the first PM at a company with that kind of novel technical approach. What was the hardest part of figuring out what to build first?
⚠ Handle carefully
- Casey moved from Director of PM at Dremio back to Principal PM at Fivetran — a title that could be read as a step back. Do not reference this directly or imply it was a downgrade; he likely made a deliberate choice for domain fit or company trajectory, and raising it would feel awkward or presumptuous.
- The Fivetran-dbt Labs integration is ongoing and the organizational picture may be unsettled — avoid questions that presuppose clean org structures or stable roadmaps, and be sensitive that Casey himself may have limited visibility into how the combined company will ultimately be organized.
- Casey has only been at Fivetran for about a year — avoid questions that assume deep institutional knowledge about Fivetran's historical product decisions or culture, as he may still be orienting himself and could feel put on the spot.