At Unusual Ventures, we believe that Data Engineering will play a critical role in enabling companies to leverage data, analytics, and machine learning within their organization.
Data engineers are the current fastest growing job with 50% YoY growth. Since 2018, there have been four times as many job postings for data engineering roles than that of Data Scientist roles.
While Data Scientists build analyses and ML models on top of big data, Data Engineers support Date Scientists and other organizations by building and maintaining the data infrastructure and pipelines. Data workflow orchestration has become an instrumental part of a Data Engineer’s workflow, with Airflow being one of the most commonly required skills among 11% of all job postings.
At the same time, various market trends—such as increased sophistication of data pipelines, event-driven and real-time use cases, and the increasing use of Machine Learning (ML)—have required an influx of new tools designed for modern architectures.
We anticipate significant growth in data engineering tools to support today’s infrastructures and use cases. Workflow orchestration tools are a core opportunity in this space and this white paper explores how founders can take advantage of them.
More specifically, this white paper will cover:
The Unusual Ventures team is excited about tools that better enable developers to orchestrate data in an increasingly complex ecosystem and we look forward to seeing the next generation of workflow orchestration tools emerge. In that vein, we’d love to hear from you if you are working on new data engineering tools: email@example.com, @jordan_segall.
This white paper will cover: The evolution of workflow orchestration tools and what prompted them, new opportunities for emerging players, and a map of contemporary solutions in the market