Real-Time Data Integration and Event Streaming Platform for Utility Optimization

High Priority
Data Engineering
Utilities
👁️2730 views
💬189 quotes
$15k - $50k
Timeline: 8-12 weeks

Our scale-up utility company is seeking an experienced data engineer to develop a real-time data integration and event streaming platform. The objective is to enhance operational efficiency and decision-making by leveraging cutting-edge data technologies. This project involves setting up a robust data mesh architecture to enable self-service data, improve data observability, and support real-time analytics across electric, water, and gas utilities.

📋Project Details

In the competitive and highly regulated utilities sector, optimizing resource usage and ensuring timely delivery are paramount. Our scale-up utility company is embarking on a project to build a real-time data integration and event streaming platform to transform how we manage data across our electric, water, and gas services. The ideal candidate will design and implement a data mesh architecture to decentralize data ownership and enable cross-functional teams to access real-time insights with ease. The project includes setting up an event streaming system using Apache Kafka to process and analyze live data streams. By incorporating Apache Spark and Databricks, we aim to achieve high-performance data processing and leverage machine learning for predictive analytics. Airflow will be utilized for workflow orchestration, ensuring seamless data pipeline operations, while Snowflake or BigQuery will serve as our data warehousing solutions to unify and store diverse data sets. The expected outcomes are improved data observability, enhanced operational efficiency, and smarter decision-making processes.

Requirements

  • Experience with real-time data integration and event streaming
  • Proficiency in Apache Kafka and Apache Spark
  • Expertise in data mesh architecture and implementation
  • Strong understanding of data observability tools
  • Familiarity with Snowflake or BigQuery for data warehousing

🛠️Skills Required

Apache Kafka
Apache Spark
Airflow
Snowflake
Databricks

📊Business Analysis

🎯Target Audience

Internal data and operations teams within the utility company, aiming to enhance operational efficiency and decision-making capabilities.

⚠️Problem Statement

The utility industry is facing challenges in managing large volumes of data generated from multiple sources, leading to inefficiencies and delayed decision-making. A real-time data platform is essential to process and analyze data promptly, ensuring optimal resource allocation and compliance with regulatory standards.

💰Payment Readiness

The utility company is ready to invest in this solution due to the significant cost savings in operational efficiency and the pressure to comply with stringent regulatory standards.

🚨Consequences

Without solving this problem, the company risks operational inefficiencies, increased operational costs, and potential non-compliance with industry regulations, leading to hefty fines.

🔍Market Alternatives

Current alternatives involve manual data processing and siloed legacy systems, which are time-consuming and prone to errors, lacking the agility and accuracy of real-time analytics.

Unique Selling Proposition

Our platform's unique selling proposition is the combination of cutting-edge technologies like event streaming and data mesh architecture, which collectively enhance data accessibility, scalability, and real-time insight generation.

📈Customer Acquisition Strategy

We plan to demonstrate the solution's capability through pilot projects and case studies, highlighting real-time efficiency gains and compliance advantages, to onboard more departments and eventually external partners.

Project Stats

Posted:July 23, 2025
Budget:$15,000 - $50,000
Timeline:8-12 weeks
Priority:High Priority
👁️Views:2730
💬Quotes:189

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