We are seeking a skilled data engineer to optimize our real-time data pipeline, enabling faster and more accurate news delivery to our audience. This project will focus on implementing advanced data engineering practices such as data mesh and event streaming to enhance our data infrastructure. By leveraging technologies like Apache Kafka, Spark, and Airflow, we aim to handle increasing data volumes efficiently and provide timely news updates across our platforms.
Our target users are tech-savvy news consumers who demand real-time updates and diverse content, including breaking news, in-depth analyses, and multimedia features.
The current data pipeline is unable to efficiently handle the increasing data volume and complexity, resulting in delayed news updates and reduced user engagement.
Market research indicates that our audience is willing to pay for faster, more comprehensive news coverage, as it enhances their decision-making processes and keeps them informed in real-time.
If this problem isn't solved, we risk losing audience trust, facing declining website traffic, and seeing a drop in subscription renewals, ultimately impacting our revenue.
Current alternatives include manual data processing, which is cumbersome and prone to errors, and using third-party platforms, which can be costly and limit customization.
Our optimized data pipeline will provide unmatched speed and accuracy in news delivery, distinguishing us from competitors and solidifying our position as a leading news source.
We will leverage targeted online marketing campaigns and partnerships with tech influencers to reach our audience, highlighting the benefits of real-time news updates and encouraging subscriptions.