How data teams are rebuilding insurance from the inside

Jason Ash, Chief of Data at Symetra, joins the show to unpack how a mid sized insurer is rebuilding its data stack and culture so business and technology actually pull in the same direction. He shares how his team brings actuaries, product leaders, and engineers into one data platform, and why opening that platform to non technical contributors has been a turning point. If you work in a regulated industry and are trying to move faster with data, this conversation gives you a very practical view of what it takes.

Key takeaways

• Business and tech only work when they share context and trust

Jason has sat in both seats, first as an actuary and now as a data and engineering leader. That dual background helps him translate between risk, regulation, and modern data practices, and it shapes how he frames projects around shared business outcomes rather than tools.

• Put data leaders inside business line leadership, not on the outside

Several of Jason’s managers sit on the leadership teams for Symetra’s life, retirement, and group benefits divisions. They hear priorities and constraints at the same time as product and distribution leaders, which lets them frame data as a value add for new products instead of a back office cost.

• Treat the warehouse as a shared product and measure contributors, not just tables

Symetra’s dbt based warehouse started with about five contributors. Over three years they grew that to more than sixty, and half of those people sit outside the core data team. Business users learn to contribute SQL, documentation, and domain knowledge directly into the repo, which spreads ownership and reduces bottlenecks.

• Shift stakeholders away from big bang launches to steady delivery

Jason pushes his teams to think like software engineers. Rather than promising a perfect data product on a single date, they deliver an early slice of data, have partners use it right away, collect feedback, and improve every month. That builds trust and avoids the usual disappointment that comes with one big release.

• Use maturity as a guide for where to invest

Early on, his group picked a few strong champions who were willing to accept slower delivery in exchange for building real infrastructure. Now that the platform and practices are in place, the focus is on scale, reuse, and getting more people to build on the same foundation, including as AI capabilities start to reshape the work.

Timestamped highlights

00:53 Jason explains what Symetra actually does and how their product mix makes data work more complex than the company size might suggest

02:19 From actuary to Chief of Data, and what sitting on both sides of the fence taught him about business and technology expectations

08:08 Why mixing data engineers, data scientists, actuaries, and analysts on the same problems leads to stronger solutions than any single discipline alone

13:44 How embedding data leaders into each business division’s leadership group changed when and how data enters product discussions

16:38 The dbt story at Symetra, and how more than sixty people across the company now contribute directly to the shared data warehouse

26:22 Moving away from big bang data launches and setting expectations around early value, continuous feedback, and ongoing quality improvements

32:06 The tension between safety and speed as AI advances, and what Jason worries about most for established insurers that move too slowly

Practical moves you can steal

• Put data leaders on business line leadership teams so they hear priorities and constraints in real time, not after the roadmap is set

• Track how many unique people contribute to your data warehouse and make that a visible success metric across the company

Stay connected

If this episode helped you think differently about data leadership in regulated industries, share it with a colleague who owns product, data, or actuarial work.