Architecture

Tell us about your background Throughout my career, I have dedicated myself to creating tools, products, and technologies that help people effectively utilize their data. My passion lies in developing products that enable users to efficiently and scalably gain maximum value from their data. My journey in understanding the intricacies of data and its potential began at Palantir Technologies, where I began working on search and indexing products. As data volumes grew, I focused my efforts on solving some of Palantir customer’s core problems across the financial and defense verticals before leading customer focused compute teams. After Palantir, I served as CTO at Veraset, a cloud-based data-as-a-service company. Veraset delivered high-quality, large scale data to a number of enterprises and grew to 15M ARR before being acquired. Following this, I joined Citadel Investment Group as the Head of Business Engineering of Ashler. In that role, I managed crucial data operations, including overseeing data pipelines, investment platforms, data lakes, and the software and data engineering teams responsible for them. ...

Managing SQL code at scale is one of the biggest challenges in data engineering. As data teams grow and pipelines become more complex, traditional approaches to SQL development quickly become unwieldy. This LinkedIn Learning course explores how dbt (data build tool) transforms the way we think about SQL development, bringing software engineering best practices to analytics engineering. Course Approach Real-World Problem Solving: Each chapter presents actual situations and challenges that data engineers face, with focused code examples showing practical solutions. ...

In this course, instructor Vinoo Ganesh gives you an overview of the fundamental skills you need to become a data engineer. Learn how to solve complex data problems in a scalable, concrete way. Explore the core principles of the data engineer toolkit—including ELT, OLTP/OLAP, orchestration, DAGs, and more—as well as how to set up a local Apache Airflow deployment and full-scale data engineering ETL pipeline. Along the way, Vinoo helps you boost your technical skill set using real-world, hands-on scenarios. ...

The data pipeline has become a fundamental component of the data science, data analyst, and data engineering workflow. Pipelines serve as the glue that links together various components of the data cleansing, data validation, and data transformation process. However, despite its importance to the data ecosystem, constructing the optimal data pipeline is generally an afterthought - if it’s considered at all. This makes any changes to the central pipeline highly error-prone and cumbersome. With the ever-growing demand for new kinds of data, especially from external vendors, constructing pipelines that are scalable and that allow for monitoring is pivotal for the safe and continued use of data. ...

Data pipelines are the foundation for success in data analytics, so understanding how they work is of the utmost importance. Join us for four hours of expert-led sessions that will give you insight into how data is moved, processed, and transformed to support analytics and reporting needs. You’ll also learn how to address common challenges like monitoring and managing broken pipelines, explore considerations for choosing and connecting open source frameworks, commercial products, and homegrown solutions, and more. ...