Speakers

Shashank Agarwal is one of the founders of Thirdwatch. After the acquisition of Thirdwatch by Razorpay, he currently heads the Thirdwatch business at Razorpay and is focused on curating a wholesome fraud solution for e-commerce businesses. He also heads engineering for the risk vertical at Razorpay. Shashank has a demonstrated history of working on Data platforms, AI/ML technologies, adTech and mobile based solutions. He is a true believer in tech innovation leadership and has developed multiple products in the past scaling them from 0 to 1. 

Use Case

Data science at scale using Apache Flink : Dynamic model serving and real-time feature generation

Agnoli Enrico is a Software Engineer at Workday. During the last 6 years, he worked on multiple technical projects as a developer, tech lead and people manager at different stages. Currently involvements:
- As architect and developer to technically lead the delivery of a new DataStreaming platform to support ML
- Investigate new technologies and deliver POC for possible new tools/products, like streaming platforms, blockchain, audibility of machine learning models and data security
- Being part of the Workday Giving&Doing foundation, he helps to organize events and raise awareness on various causes / nonprofit groups.
Studied at Politecnico of Milan and moved to Germany right after to work first on Honda’s ASIMO humanoid robots, then on automation software in one of Europe biggest datacenter for Amadeus and finally for Workday, #1 Future Fortune company of 2018. Workday's innovator of the year in 2018 for a research project on Blockchain.

Use Case

Flink @WORKDAY: scaling of ingestion data pipelines to S3

Haseeb Asif is a dual degree master student at the KTH Royal Institute of Technology, Stockholm, and TU Berlin. His primary focus of work is in distributed systems and Data intensive processing. He wrote his master thesis on External Streaming State Consistency and Processing Guarantees for Apache Flink. His research work is focused on performance optimization of state backends. In particular, stream processing using modern data stream processing engines, i.e. Apache Flink.

Ecosystem

FlinkNDB : Skyrocketing Stateful Capabilities of Apache Flink

Girish manages Flink, Pinot, and Presto teams at Uber. Before that, he spent over a decade optimizing resources, search ads, and geo data analytics at Google, interrupted by a brief start-up stint at Urban Engines. He has a PhD in Computer Science and an MS in Math from UIUC.

Community and Industry Impact

Powering OLAP at Uber using Apache Flink

Niels Basjes (1971) has been working for bol.com since May 2008. Before that he was working as a Webanalytics architect for Moniforce, and as an IT architect/researcher at the National Aerospace Laboratory in Amsterdam.

Since the second half of the 1990s he has been working on processing problems that require scalability. He has applied these concepts in the past 15 years in aircraft/runway planning, IT operations and in the field of web analytics to build reports for some of the biggest websites in the Netherlands.

Also at bol.com the primary focus of Niels Basjes are scalability problems and he is responsible for a shift in thinking about data and the business value it contains. Niels designed and implemented many of the personalisation algorithms that are in production today at bol.com.

Niels studied Computer Science at the TU Delft, and has Business administration degree at Nyenrode University.

Niels is an active opensource developer who is one of the Apache Avro PMC members and has authored ( https://github.com/nielsbasjes/ ) and contributed various improvements and bugfixes to projects like Hadoop, HBase, Pig, Flink, Beam and Storm.

Operations

When your stream doesn’t stream very well

Technology Deep Dive

Disco: Efficient Distributed Window Aggregation

I’m Jeremy Ber, and I have been working in the telemetry data space for the past five years as a Software Engineer, Machine Learning Engineer, and most recently a Data Engineer. At Amazon Web Services, I am a Solutions Architect Streaming Specialist supporting both Managed Streaming for Kafka and Kinesis services. I love all things real-time, and Apache Flink is a passion of mine. My dream is that one day batch and streaming will be unified!

Enriching your Data Stream Asynchronously with Apache Flink

Austin Cawley-Edwards is a Senior Software Engineer at FinTech Studios, using real-time data to bring clarity to financial news. He frequently works with Apache Flink, RabbitMQ, and Elasticsearch. He also loves API design, taking part in collaborative communities, and sometimes JavaScript.

Use Case

Getting Started with Flink for Small Teams w/ RabbitMQ and Kubernetes

Shahid Chohan is a software engineer on Stripe’s Streaming team where he works on a number of real-time data infrastructure initiatives, including operating Flink as a platform for Stripe’s engineers. Prior to joining Stripe, Shahid worked on change-data-capture, real-time data-warehousing, and real-time experimentation systems at Yelp.

Technology Deep Dive

Streaming, Fast and Slow: Mitigating Watermark Skew in Large, Stateful Jobs

Michał Ciesielczyk is the Head of AI Engineering at Deep.BI. He is responsible for researching, building and integrating machine learning tools with a variety of technologies including Scala, Python, Flink, Kafka, Spark, and Cassandra. Previously, he worked as an assistant professor at the Poznan University of Technology, where he received a Ph.D. in computer science and was a member of a research team working on numerous scientific and R&D projects. He has published more than 15 peer reviewed journal and conference papers in the areas of recommender systems and machine learning.

Use Case

Using Flink for Versatile Feature Engineering Pipelines

Stephan Ewen one of the original creators and PMC Chair of Apache Flink, and CTO and co-founder of Ververica (recently acquired by Alibaba Group). Stephan leads the development and direction of Apache Flink inside Ververica, following the vision to build the next generation architecture for data analytics and distributed applications, powered by stream processing technology.

Before working on Apache Flink, Stephan worked on in-memory databases, query optimization, and distributed systems. He holds a Ph.D. from the Berlin University of Technology.

Technology Deep Dive

Fault Tolerance 2.0 for Apache Flink

Leire has been a Software Engineer at Workday for the last 5 years, although it has been over a decade that she is immersed into Software development, performing multiple roles as developer, tech lead and mentor.

Leire is passionate about building quality code, from conception through implementation, testing and delivery. Being the newest member of the Data Streaming Platform team in Workday, she's excited to be given the opportunity to work with Apache Flink and explore the possibilities and challenges that it has to offer.

When not behind a computer, Leire enjoys ‘all things outdoors’, with a bit of circus arts on the side.

Use Case

Flink @WORKDAY: scaling of ingestion data pipelines to S3

Gyula is a Software Engineer in the Flink Engineering team at Cloudera working on integrating Flink into the Cloudera platform.

He has been a committer and contributor since the early days of Flink streaming and has used Flink in large scale production at King for almost 4 years delivering innovative real-time applications at a global scale.

Gyula grew up in Budapest where he first started working on distributed stream processing and later became a core contributor to the Apache Flink project. Gyula has been a speaker at numerous big data related conferences and meetups, talking about stream processing technologies and use-cases.

Ecosystem

End-to-end Flink SQL with Schema Registry, Kafka & Kudu

Addison Higham is a software engineer and community manager at StreamNative and contributor to Apache Pulsar. Previously, Addison was at Instructure where he led a team to build a data and analytics platform powered by Flink and Pulsar. With this past experience, Addison is helping to implement the next set of features in Pulsar to enable comprehensive support for batch workloads.

Ecosystem

Flink + Pulsar: The Path To Unified Batch and Streaming 

Zhenqiu Huang is a senior software engineer at Uber. He worked the Unified Streaming and Batch using Flink SQL for high data quality streaming use cases at Uber. Now, he is mainly working on unified AthenaX and FaaS job deployment and management in heterogeneous compute environment (Prim DC and Cloud) at Uber.

Operations

Building Unified Streaming Platform at Uber

Fabian Hueske is a committer and PMC member of Apache Flink. He is one of the three original authors of the Stratosphere research system, from which Apache Flink was forked in 2014. Fabian is a co-founder of data Artisans (now Ververica), a Berlin-based startup devoted to fostering Flink, where he works as a software engineer and contributes to Apache Flink. He holds a PhD in computer science from TU Berlin and is a co-author of "Stream Processing with Apache Flink".

Production-Ready Streaming SQL with Ververica Platform

Nick leads the Stream Processing Platform team as a part of the Intuit Data Platform. He focuses on providing self-serve and low-barrier access to state-of-the-art stream processing technologies throughout Intuit. Previously, Nick has also applied big data technologies to trust and safety (at Reddit) and predictive marketing (at Radius Intelligence).

Use Case

Build Streaming Processor platform On Flink

Simba Khadder is a product leader with a strong engineering background. He has worked as a software engineer at Google where he worked on Cloud Datastore and Search. At StreamSQL, he leads a team delivering the next generation of datastore built on event-sourcing. He's a published astrophysicist for his work on finding Planet 9 and ran the SF marathon in basketball shoes.

Use Case

Feature Stores: Powering Machine Learning Infrastructure with Apache Flink

Jeongmin Kim is a software developer at Hyperconnect. As a real-time data application developer, Kim is working on the matchmaking system, feature store, and recommendation system of Azar with streaming data pipelines using Flink.

Operations

On-demand low-latency feature generation at Hyperconnect

Ajit Koti is a Senior Engineer on the Growth Data Engineering team at Netflix, building distributed data processing systems. He has over 15 years of experience in building and architecting large-scale distributed systems and high frequency trading systems. Ajit has previously worked for Fanatics, IBM Labs and J P Morgan.

Use Case

Tale of Stateful Stream to Stream Processing

Aljoscha Krettek is a co-founder at Ververica where he works on the Flink APIs in the open source. He is also a PMC member at Apache Flink and Apache Beam. Before working on Flink, he studied Computer Science at TU Berlin, he has worked at IBM Germany and at the IBM Almaden Research Center in San Jose. Aljosch has spoken at Hadoop Summit, Strata, Flink Forward and several meetups about stream processing and Apache Flink before.

Technology Deep Dive

Unified Flink APIs at Last

Nico Kruber is an Apache Flink committer, working as a Solutions Architect at Ververica where he is helping our clients and the open source community to get the most out of Apache Flink. For this, Nico can leverage his in-depth knowledge of Flink, Ververica Platform, and the expertise of our team. Before joining Ververica, Nico was working on his PhD in parallel and distributed systems at the Zuse-Institute Berlin and was developing a transactional key-value store.

Use Case

A Year in Flink - Flink SQL Live Coding

Sruthi Sree Kumar is a dual degree master student at the KTH Royal Institute of Technology, Stockholm, and TU Berlin. She is also a research intern at Research Institutes of Sweden (RISE) where her primary focus of work is in distributed data processing systems. She wrote her master thesis on External Streaming State Abstractions and Benchmarking. Her research work is focused on performance improvement of Flink state backend.

Ecosystem

FlinkNDB : Skyrocketing Stateful Capabilities of Apache Flink

Jingsong is a committer of Apache Flink and Apache Beam, he is a senior engineer at Alibaba.
Since 2014, he has focused on the research and development of streaming computing within Alibaba.
Since 2017, he has focused on the development of Alibaba Blink, and also contributed Apache Flink community actively.

Recently, he mainly focuses on unifying streaming and batch using Apache Flink in data warehouse architecture.

Ecosystem

Flink SQL: Unified Streaming and batch for hive integration

Rui Li is a software engineer at Alibaba and a PMC member of Apache Hive. He focuses on Flink SQL and the Flink-Hive integration feature. Before joining Alibaba, he had worked at Intel and IBM and had experience with several Apache projects including Apache Hive, Apache Spark, etc.

Ecosystem

Flink SQL: Unified Streaming and batch for hive integration

David is a solution architect with a proven record building distributed architectures and big data and fast data solutions. His recent achievements include a real-time fraud monitoring engine for instant payment or a lambda-like architecture for collecting, processing and storing data collected from thousands of smart cameras and sensors. David holds a PhD in information science from the Free University of Brussels (ULB).

Use Case

Metamodelization and Automatic Generation of ML Pipelines

System architect and lead developer at Trackunit, Denmark Started with Flink 1.2 and build Trackunit IoT platform. Worked with other big data projects. Build large distributed database systems with Microsoft SQL server.

Use Case

Alert detection in IoT using broadcast state

Pradeep Nethagani is a software engineer on the Trust and Safety team at Yelp focused primarily on bot detection. Previously, he worked at Skyhigh Networks building data pipelines for real time anomaly detection in cloud services. His interests lie in distributed systems, algorithms and various ML methodologies.

Use Case

Realtime bot detection with Flink

Jacob Oh is a senior software engineer and team leader at Hyperconnect. Data Application Team is designing, developing and maintaining Hyperconnect's Recommendation Engine (Such as Azar's matchmaking system). Hyperconnect is the company serving the services like Azar based on Real-time Communication and ML Tech. With the experiences on researching UX and engineering Applications, He design and develop the products to make a better service experience.

Operations

On-demand low-latency feature generation at Hyperconnect

Marta is a Developer Advocate at Ververica (formerly data Artisans) and a contributor to Apache Flink. After finding her mojo in open source, she is committed to making sense of Data Engineering through the eyes of those using its by-products. Marta holds a Master’s in Biomedical Engineering, where she developed a particular taste for multi-dimensional data visualization, and previously worked as a Data Warehouse Engineer at Zalando and Accenture.

Use Case

Building an End-to-End Analytics Pipeline with PyFlink

As a Lead consultant at ThoughtWorks with over 14 years of industry experience, Arti is responsible for architecting and building enterprise data solutions, providing advisory to clients in multiple strategic initiatives. In the past she has led the efforts of building multiple data-driven initiatives like scaling a high-volume data processing pipeline for radio telescope, creating recommendation engine for retail domain and re-architecting the enterprise application echo system for financial customers.

Use Case

A journey of scaling high-volume low-latency stateful processing

Fabian is a software engineer at Ververica. He is part of the team responsible for developing the Ververica Platform.
He received a Master’s degree from the Hasso Plattner Institute in Potsdam, where he researched adaptive stream processing with Apache Flink.

Operations

Towards a Flink Autopilot in Ververica Platform

Chen is working on the Pinterest streaming platform, Xenon. Previously, he contributed to Flink open source and introduced Flink to Uber in 2016. He had been working on Spark and XGBoost project and helped Uber run large scale training since 2018.

Operations

Growing a managed Flink streaming platform from scratch

Hari Rajaram is a Principal Data Architect at AWS with a proven record of designing and developing complex steaming and analytics applications. His primary role is to help customers find meaningful insights from data in real-time. He has authored a book on Apache Flink (early stages in 2016). Before joining AWS, he played an instrumental role in designing analytic applications that could scale petabytes, apart from researching data privacy.

Enriching your Data Stream Asynchronously with Apache Flink

Lakshmi is a software engineer on the streaming platform team at Lyft. The team builds and supports the core infrastructure that enables several product teams at Lyft to easily and reliably spin up Flink jobs to perform aggregations on real-time data. Most recently, she has been spending time re-architecting the platform to a Kubernetes based deployment. Prior to Lyft, Lakshmi worked in fin-tech land, building a search and information retrieval platform for Goldman Sachs.

Operations

Zero-downtime upgrades of Flink applications

Solving data processing at scale at Spotify. I'm an active open source contributor for projects spanning the areas of functional programming, type systems, tooling, and infrastructure.

Ecosystem

Data processing at Spotify - Why portability matters

Qingsheng (Patrick) Ren is currently a software engineer at Alibaba, focusing on Apache Flink ecosystem such as Apache Kafka connector and change data capture in database system. He received his Master's degree from Carnegie Mellon University and Bachelor's degree from Zhejiang University.

Ecosystem

Change Data Capture and Processing with Flink SQL

Gaël has been a software developer for more than 15 years - and has successfully avoided becoming a manager during most of that time. He’s done IT consulting for big companies for a decade before going into start-ups. He’s usually the one at DataDome who likes refactoring stuff, teaching about Scala, and finding the most elegant way to implement a feature. In his free time, he likes coding on his Open Source projects and reading pretty much any science book he gets his hands on.

Technology Deep Dive

Handling frequent changes in state structure

Till is a PMC member of Apache Flink and software engineer at Ververica. His main work focuses on enhancing Flink’s scalability as a distributed system. Till studied computer science at TU Berlin, TU Munich and École Polytechnique where he specialized in machine learning and massively parallel dataflow systems.

Technology Deep Dive

News from Flink’s engine room: “Full steam ahead”

Passionate about data processing and analytics, Flink and Kafka in particular; dedicated microservices and distributed computing architect; moonlighting developer; early adopter of Linux and contributor to open source projects.

Over 15 years in Financial Services organisations (HSBC, Lloyds Banking Group, Citibank, BBVA) and Tech companies (Hortonworks, Nokia, EMC). Co-Founder of HUMN.AI in 2017.

Use Case

Sampling and Modelling the World in Real-Time for Mobility

Venkata Sanath Muppalla is a senior software engineer at Uber. He worked on building self serve work orchestration platform and realtime pipelines using Flink for high data quality streaming use cases at Uber. Now, he is mainly working on a scalable storage solution for streaming applications in a heterogeneous computing environment (Prim DC and Cloud) at Uber.

Operations

Building Unified Streaming Platform at Uber

Caito is a software engineer in Portland, Oregon who most recently worked on New Relic's main stream processing team. She has presented about this work at various meetups and conferences (in the US and Europe). Outside of tech, she loves running, woodworking, and terrible puns.

Technology Deep Dive

Flink in the Beam World

Kelly is a member of Zillow's data streaming platform team where he has spent the last year driving Flink and Kafka adoption across the company.

Ecosystem

How We’re Democratizing Stream Processing at Zillow

Use Case

Cluster Serving: Distributed Model Inference using Apache Flink in Analytics Zoo

Chinmay Soman has been working in the distributed systems domain for the past 10+ years. He started out in IBM where he worked on distributed filesystems (NFS) and replication technologies. He then joined the Data Infrastructure team in LinkedIn and worked on Voldemort – an open source distributed key-value store, as well as Apache Samza. He’s currently a Senior Staff Software Engineer in Uber where he leads the Streaming Platform team. This team is responsible for building a pub-sub messaging infrastructure and real time analytics platform.

Community and Industry Impact

Powering OLAP at Uber using Apache Flink

Mr. Song Jiaming is now Machine Learning engineer at Intel. He is a key contributor to open source Big Data + AI project Analytics Zoo. He is now focusing on the development of Cluster Serving.

Use Case

Cluster Serving: Distributed Model Inference using Apache Flink in Analytics Zoo

Tim Spann is a Field Engineer at Cloudera where he works with Apache NiFi, MiniFi, Kafka, Apache Flink, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a senior solutions architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.

Community and Industry Impact

Using the Mm FLaNK Stack for Edge AI (Flink, NiFi, Kafka, Kudu)

Xuannan is a software engineer at Alibaba. He is focusing on the development of Apache Flink and its ecosystem after he received his master's degree from Carnegie Mellon University in 2019.

Ecosystem

Introducing Tensorflow on Flink

Menglei is a Senior Software Engineer at Houzz. He is responsible for a wide range of data projects including Flink infrastructure and its applications, logging data pipeline & observability, mobile data engineering. Prior to this, Menglei worked at Blackrock focusing on the data pipeline and storage.

Use Case

Flink powers Houzz Realtime Pipeline and Applications

Julien has been working with Scala and contributing on various open-source projects for the past 10 years. Since 2018, he is working for Spotify as a Data Engineer in the Data & Insight tribe, building libraries and tooling used in most of Spotify's data pipelines.

Ecosystem

Data processing at Spotify - Why portability matters

Big Data Engineer at Rapido, India’s Largest Bike Taxi

Use Case

Real-Time ML Applications at Scale with Flink and Beam on Kubernetes and GCP

Balazs is an intern in the Flink Engineering team at Cloudera. His spring internship project involved contributing to the Bahir Kudu connector, and exploring its use cases in SQL pipelines. He continues to learn and develop his interests in stream processing and distributed systems.
He is involved in research projects at the university. He has recently been working on the automated refactoring of concurrent and distributed programs.

Ecosystem

End-to-end Flink SQL with Schema Registry, Kafka & Kudu

For the last 3 years I've been working with Apache Flink framework in the Infrastructure team. 

Provide infrastructure support for several research teams that build Anomaly Detection Engine.

About 10 years of experience with Big Data distributed frameworks such as Spark, Hadoop, Flink, and NoSql databases.

Had various engineer and tech lead roles for big data projects at companies like Akamai, Liveperson, Amadesa.

Use Case

Load Imbalance

Manuela drives the product vision for the self-serve, managed Stream Processing Platform based on Apache Flink and Apache Beam. The Stream Processing Platform is used by Intuit Data/ML Engineers and Data Scientists to accelerate development of streaming applications which drive personalization, fraud detection, and ML insights across Intuit products.

Use Case

Build Streaming Processor platform On Flink

Seth Wiesman is a Solutions Architect at Ververica, where he works with engineering teams inside of various organizations to build the best possible stream processing architecture for their use cases.

Use Case

Hands-on Stateful Serverless Applications with Kubernetes and Stateful Functions

Jark Wu is a committer and PMC member of Apache Flink. He works as a software engineer at Alibaba and contributes to Apache Flink since 4 years ago. In Flink, he is mainly working on the Table & SQL API. Prior to Flink, Jark worked on JStorm which is a Java-version Apache Storm in Alibaba.

Ecosystem

Change Data Capture and Processing with Flink SQL

Andrey is an Apache Flink Committer and a Software Engineer at Ververica. Andrey’s work focuses primarily on Apache Flink’s distributed coordination and deployment. Previously, he worked at T-Mobile building a large scale infrastructure for batch and real-time analytics of customer experience.

Operations

Flink's New Dockerfile: One File to Rule Them All

Krzysztof is an architect, engineer and an entrepreneur passionate about solutions that take advantage of Big Data technologies. Working with distributed systems, analytics and machine learning for over 11 years, previously in companies like Netezza/IBM or Hadapt/Teradata and other startups. Finally, with others like him he found a company Getindata that offers services in building data-driven solutions where he plays the CTO role. But he likes to work full-stack going from nailing the business problem to architecting a solution to engineering it down and to installing, troubleshooting and monitoring. For 6 years he specializes in building scalable real-time analytics solutions.

Use Case

CEP platform handling millions of users - lessons from 3 years in production

Piing Zou is a Principal Engineer who is an architect at the Intuit Data Platform organization leading the Streaming Processor Platform. She also worked at Intuit Kubernetes and Intuit open-source machine learning anomaly detection/auto-scaling projects.
Before that Ping Zou is Sr. Principal Engineer at PayPal and eBay led, designed and implemented Unified Monitoring Platform, mobile payment, Cloud PaaS, Messaging Infrastructure, and e-commerce application.

Use Case

Build Streaming Processor platform On Flink