Panel: What's in store of the future of data engineering?

With budgets tightening and data use cases skyrocketing, how can data engineering teams set themselves up for success in 2023?

In this panel conversation, Shane Murray, Field CTO at Monte Carlo, Brandon Beidel, Director of Product Management, Red Ventures, and Eric Callahan, Sr. Data Consultant at Pickaxe Foundry and former Head of Data at Understood, will discuss their predictions for the year’s top challenges - and opportunities - facing data engineering teams in the New Year.

Their conversation will include the future of BI tooling, operationalizing distributed environments like data mesh, implementing data quality initiatives like data contracts, making the case for data with your finance team, and other pressing considerations.


Eric Callahan

Sr. Data Consultant


Brandon Beidel

Director of Product Management


Shane Murray

Field CTO


What is the cost to attend and watch the virtual sessions?

Data Team Summit is always free and open for all to attend.

What is Data Teams Summit?

This year, we've taken the peer-to-peer empowerment of data teams one step further and formally transformed DataOps Unleashed into Data Teams Summit to better reflect our focus on the teams and individuals running, managing, and monitoring data pipelines.

Data Teams Summit is an annual, full-day virtual conference, led by data rockstars at future-forward organizations about how they're establishing predictability, increasing reliability, and creating economic efficiencies with their data pipelines.

We'll be back again in 2024 and look forward to another round of data team focused conversations.

Who comes to Data Teams Summit?

Data professionals and experts including data engineers, administrators, architects, analysts, AI/ML professionals, and relevant data technology leadership.

Join us for sessions on:

  • Data teams & best practices
  • Data pipelines & applications
  • DataOps observability
  • Data quality & data governance
  • Operations observability
  • MLOps
  • Data modernization & architecture
  • Biz/FinOps observability

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