Building a Scalable Real-time Data Pipeline for Enhanced Customer Insights

Medium Priority
Data Engineering
Data Analytics
👁️18364 views
💬821 quotes
$50k - $150k
Timeline: 16-24 weeks

An enterprise company seeks to develop a robust real-time data pipeline to enhance customer insights and improve decision-making. By implementing cutting-edge data engineering practices, the company aims to leverage real-time analytics and data mesh architecture to gain competitive advantages.

📋Project Details

Our enterprise company is embarking on a significant transformation to harness the power of real-time analytics and data mesh architecture. The project aims to construct a scalable real-time data pipeline that enhances customer insights across multiple touchpoints. This initiative requires the integration of advanced technologies such as Apache Kafka for event streaming, Spark for data processing, and Airflow for orchestrating complex workflows. The project will also implement dbt for data transformations and Snowflake for a cloud data warehousing solution, ensuring seamless data flow and accessibility. By utilizing Databricks to streamline MLOps and BigQuery to perform advanced analytics, we aim to provide our analytics and marketing teams with unprecedented data observability and insights. This initiative is not only about refining current capabilities but also about establishing a framework that supports future scalability and innovation. With a budget of $50,000 to $150,000 and a timeline of 16-24 weeks, the project is positioned to drive strategic decision-making and foster deeper customer engagement.

Requirements

  • Experience with real-time data processing
  • Proficiency in cloud data warehousing solutions
  • Ability to integrate MLOps practices
  • Expertise in data mesh architecture
  • Strong background in data observability

🛠️Skills Required

Apache Kafka
Spark
Airflow
dbt
Snowflake

📊Business Analysis

🎯Target Audience

The target users are enterprise-level analytics teams and marketing departments seeking to leverage real-time customer insights for strategic decision-making and enhanced engagement.

⚠️Problem Statement

The current data infrastructure is insufficient for handling real-time analytics, leading to delayed insights and missed opportunities in customer engagement. Solving this issue is critical to maintaining competitive advantages.

💰Payment Readiness

The market is ready to invest in solutions that offer competitive advantages, cost savings through operational efficiencies, and improved decision-making processes.

🚨Consequences

Failure to address this issue may result in lost revenue opportunities, reduced customer satisfaction, and a competitive disadvantage in the marketplace.

🔍Market Alternatives

Current alternatives include traditional batch processing systems that lack the agility and responsiveness required for real-time insights, positioning them as less effective in dynamic market environments.

Unique Selling Proposition

Our solution's unique selling proposition is its ability to provide real-time data insights through a scalable, future-proof architecture, leveraging the latest in data streaming and cloud technology.

📈Customer Acquisition Strategy

The go-to-market strategy involves leveraging the existing enterprise client base, showcasing case studies, and providing trial access to demonstrate the solution's impact on enhancing customer insights and decision-making.

Project Stats

Posted:July 21, 2025
Budget:$50,000 - $150,000
Timeline:16-24 weeks
Priority:Medium Priority
👁️Views:18364
💬Quotes:821

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