Engaging Talks

Our talks are backed by our 100% No Bullshit Guarantee* and delivered by leading data scientists and engineers from top organizations like Facebook, Netflix, Lyft, Databricks, LinkedIn, Stanford University & many more.


6 Unique Tracks

This year, we will be offering 6 unique and exciting tracks, including: Data Engineering & Beyond, Data Science & Analytics, ML Infrastructure, AI Products, Lightning Talks, and a series of peer-led Workshops.


We are a diverse group of geeks, coders, scientists, analysts, and more. We care deeply about local data communities, no big $$$ sponsors here, just data nerds, like you & I.            


Born To Be Open Source

We believe in Open Source; code, content and mentality. We feature top open source contributors and tools at our talks. Afterwards, we publish all content (talks and slides) for the community, for free.


Participate in Workshops

Experience a two-day track dedicated fully to peer-led Workshops, for free. Try out the latest products alongside their creators, get hands on experience with innovative tools, and meet some of the most talented builders in our industry. 


Networking That Works

Experience our popular "Speaker Office Hours" format to interact directly with each speaker after their talk. Office hours, Workshops, and our Data Community Party allow you to meet data influencers who will positively impact your career.

Austin 2022 Track Hosts

Daniel Francisco

VP of Product


David Aronchick

Co-director of Research

Protocol Labs

Masha Danilenko

Data Engineer

Meta (Facebook)

Sean Taylor

Data Science Manager


Shinji Kim

Founder & CEO

Select Star

Austin 2022 Speakers

Willy Lulciuc

Founding Engineer


Max Beauchemin


Preset Labs

Julien Le Dem

Co-Founder & CEO


Vinoth Chandar

VP, Apache Hudi

Apache Software Foundation

Benn Stancil

Chief Analytics Officer


Abe Gong

Co-Founder & CEO


Tejas Manohar

Founder and Co-CEO


Caitlin Colgrove

Founder & CTO


Jessica Laughlin

Strategic Initiatives Lead


Hung Dang



Chetan Sharma

Founder & CEO


Emily Curtin

Senior Machine Learning Engineer


Danny Chiao

Engineering Lead


Kyle Eaton

Growth Lead


Ville Tuulos

CEO, Co-Founder


Egor Gryaznov

Co-Founder and CTO


Yaroslav Tkachenko

Staff Data Engineer


Seth Rosen

CEO, Co-Founder

TopCoat Data

Devin Petersohn

Co-Founder and CTO


Anand Ranganathan

Co-Founder & Chief AI Officer


Jules Damji

Lead Developer Advocate


Clodéric Mars

VP of Engineering


Paula Griffin

Director of Product

Zip Recruiter

Chad Sanderson

Head of Product, Data Platform


Anupam Datta

Co-Founder, Chief Scientist


Sandy Ryza

Software Engineer


Niels Bantilan

Machine Learning Engineer


Francesca Lazzeri

Principal Data Scientist Manager


Stayed tuned for more speakers...

Conference Committee

Pete Soderling

Pete Soderling - Chair

Pete Soderling is the founder of Data Council and the Data Community Fund. As a former software engineer, repeat founder and investor in more than 40 data-oriented startups, Pete’s lifetime goal is to help 1,000 engineers start successful companies. Most importantly, Pete is a community builder — from his earliest days of working with the data engineering community starting in 2013, he has witnessed the unique power of specialized networks to bring inspiration, knowledge and support to technical professionals. 


Previously, Pete founded Hakka Labs (a social network for software engineers), Stratus Security (an early cloud-based API platform) and mechanikal (a software development agency in NYC). He is a graduate of New York University, has spoken at events such as TEDx, O’Reilly Strata and QCon, and has worked actively in supporting technical founders around the globe.

Oana Olteanu

Oana Olteanu - Co-Chair

Oana is an ML engineer with operating experience in enterprise software and investment experience at the Seed, Series A and Series B stages. She is currently a Principal at SignalFire strengthening their technology portfolio with a focus on seachange technologies across the software stack. 

Prior to VC, Oana worked at SAP where she contributed to the development of the backend systems used by SAP for its solution portfolio. She also developed assessment frameworks and evaluated requests for funding from more than 70 product teams, across different stages of the life cycle. 

Oana received a BS in Computer Science with a specialization in Machine Learning from Jacobs University and an MS in Computer Science and Business with specialization in Machine-to-Machine Platforms from Mannheim University.

Austin 2022 Conference Tracks

Data Engineering and Beyond

The bread and butter of Data Council, this track focuses on modern data engineering workflows, storage systems, design patterns and more. We feature top speakers who are thought leaders in the data engineering community, authors of many of the OSS tools you already use, or both!

Themes in this track are centered around the most important pieces of the data pipeline workflow: data-ops, data quality, ingest & ETL/ELT, monitoring, metadata and more. Learn best practices from top teams & startups who have built rock-solid processing architectures to handle data at internet scale. 

This track will appeal to hands-on data engineering practitioners who fluidly cross the boundary between development and operations

Data Science and Analytics

The Data Science & Analytics track focuses on the tools and algos of the analytically inclined, covering topics such as Business Intelligence (BI), customer analytics, A/B testing and data visualization, plus talks on tools and techniques that are applicable for practicing data scientists and analytics professionals. 

If you’re interested in the latest advancements in statistical methods, data science notebooks, AI explainability or algorithmic insights, join your data science peers on this track to learn about recent innovations in this space that highlight applied data science skills and solutions.

ML Infrastructure

The ML Infrastructure track focuses on the engineering behind existing and novel machine learning systems, frameworks and tooling. Geared towards ML engineers, we focus on the layer of tooling & infrastructure that enables data scientists to create, test, deploy and monitor their models in production.  

In this track you’ll learn about topics such as data preparation, feature engineering, model quality & monitoring, ml-ops, and best practices in generalizing ML workflows. 

Visit the talks in this track to develop a more mature understanding of how the best data teams on the planet think about the embodiment of their data science and ML algos inside maintainable production systems.

AI Products

The AI Products track demonstrates the intersection of applied data science/ML methods in product form, covering topics such as full-stack product development of data-oriented products, product-based implementations of new research methods, and features powered by machine learning inside products (i.e. recommendation systems, NLP based features, scoring, etc.). 

This is a product-focused track where talks are given by technical founders or product managers with a technical background who are advancing the future of data & AI inside real-world digital products.

Lightning Talks

The Lightning Talks track features 15-minute presentations from some of the most cutting-edge startups in our industry. With 12 different speakers participating, this track will provide a unique view of where data-oriented startups are headed, and the technologies they’re built on, across a wide variety of applications. Lightning talks will be intermittently broken up by networking breaks that allow attendees to directly follow up with the presenters they found most compelling. Expect this track to be highly diverse and interactive. 


This 2-day track is dedicated to peer-led Workshops that attendees can experience throughout the event, for free. Try out the latest products alongside their creators, get hands-on experience with innovative tools and meet some of the most talented builders in our industry. 

Featuring: Census (operational analytics), Rudderstack (OSS CDP), Starburst (MPP database), Soda (data monitoring), Rasgo (OSS feature engineering), Carto (geospatial database) and Y42 (low-code data platform).


Apr 17, 2019 1548320400000

Welcome, announcements & track host intros (Pete Soderling)

Apr 17, 2019 1548321300000

Keynote 1

Apr 17, 2019 1548324000000

Talk 1

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What Our Attendees Say

It's no secret that Data Council has been one of my favorite conferences, as it is for many other data professionals. Data Council is unique because it's organized by technical experts, for technical experts. While there are great conferences to discuss academic research, there are few where you can hear from the next generation of data experts in the industry, and at Data Council, the speakers are almost exclusively the founders of some of the most disruptive startups in the space. 

Jennifer Prendki

Founder & CEO

Jennifer Prendki
Just wanted to reach out to thank you for the opportunity to speak at the conference. As a conference it was very informative and the talks inspired some of my software design approaches. I'm sharing my experiences with my team to help spread the knowledge.

Neelesh Salian

Senior Software Engineer
Stitch Fix

Neelesh Salian
Thanks for organizing Data Council. I really enjoyed the conference! I think you managed to build something with the right balance of tech and business content. Definitely one of the best conferences I attended this year. Not only that the talks were valuable but I enjoyed speaking to other participants. I found that many of them face similar challenges to the ones we deal with on a daily basis. Looking forward for the next one.

Gideon Mendels

Co-founder & CEO, Comet.ml

Gideon Mendels

Austin 2022 Partners


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Conference Venue

Austin Convention Center

  •    Data Council will be held at the AT&T Hotel and Conference Center inside UT Austin
  •    Proof of vaccination against COVID-19 will be required at entry
  •    Spacious venue allows for social distancing
  •    We will comply with all city health mandates at the time of the event

    Address: 1900 University Ave, Austin, TX 78705 
    Get directions

Register For Data Council Austin 2022