Our SME in the Information Technology sector is seeking an experienced data engineer to develop a scalable data pipeline that enables real-time analytics. The project aims to improve decision-making processes by integrating Apache Kafka, Spark, and Snowflake to handle large volumes of data efficiently.
Our target audience includes internal stakeholders who rely on real-time data for operational and strategic decision-making, as well as external clients who benefit from enhanced service delivery.
Our current data infrastructure fails to support the real-time analytics required for competitive decision-making, which limits our ability to respond to market changes promptly.
The market is ready to invest in this solution due to the competitive advantage offered by real-time analytics, which leads to faster decision-making and improved service offerings.
If the problem isn't solved, we risk losing out on opportunities to enhance our market position due to slower decision-making processes and reduced customer satisfaction.
Existing alternatives involve batch processing, which lacks the real-time capabilities needed for immediate insights and action. Competitors may already have more advanced data infrastructures.
Our solution's unique selling proposition is the integration of best-in-class technologies such as Kafka and Spark, offering a seamless real-time analytics experience that is both scalable and efficient.
We plan to leverage digital marketing channels and industry partnerships to reach potential clients who require advanced data analytics capabilities, while promoting the successful implementation of our real-time pipeline as a case study.