Next-Gen Real-Time Data Pipeline for Enhanced Financial Insights

Medium Priority
Data Engineering
Banking Financial
👁️18414 views
💬757 quotes
$50k - $150k
Timeline: 16-24 weeks

We are seeking an experienced data engineer to design and implement a cutting-edge real-time data pipeline for our banking operations. The goal is to enhance financial insights and decision-making by leveraging the latest technologies in data engineering. This project will involve integrating various data sources using event streaming and implementing a data mesh architecture to ensure high data quality and observability.

📋Project Details

As a leading enterprise in the Banking & Financial Services industry, we need to stay ahead in providing timely and accurate financial insights. Our current batch processing architecture does not meet the growing demands for real-time data access and analytics. We are looking for a data engineering expert to build a next-gen data pipeline. The project involves setting up an event streaming platform using Apache Kafka to capture and process data in real-time from multiple financial systems. Spark and Airflow will be used for data processing and workflow orchestration, ensuring efficient data flow and transformation. The project will also establish a data mesh architecture, enabling domain-oriented decentralized data ownership and improving data quality and observability. Snowflake and BigQuery will be integrated for scalable data storage and analytics, while dbt will be employed for data transformations. The end goal is to enhance data accessibility and provide faster, more accurate insights to our financial analysts.

Requirements

  • Proven experience in building real-time data pipelines
  • Expertise in event streaming and data mesh architecture
  • Familiarity with data storage solutions like Snowflake or BigQuery
  • Strong understanding of MLOps and data observability
  • Ability to work in a collaborative enterprise environment

🛠️Skills Required

Apache Kafka
Spark
Airflow
dbt
Snowflake

📊Business Analysis

🎯Target Audience

Our target audience includes financial analysts, risk managers, and decision-makers within the banking sector who rely on timely insights for strategic planning, risk assessment, and compliance reporting.

⚠️Problem Statement

Our current batch processing system limits the ability to provide real-time financial insights, impacting timely decision-making and competitive agility. The lack of real-time data access poses a risk of delayed responses to market changes.

💰Payment Readiness

The banking sector is under increasing pressure to improve operational efficiency and compliance, driving a strong demand for real-time analytics solutions that can deliver immediate business value and enhance decision-making capabilities.

🚨Consequences

Failure to implement a real-time data pipeline could result in lost revenue opportunities, increased compliance risks, and a significant competitive disadvantage in adapting to market changes quickly.

🔍Market Alternatives

Current alternatives involve traditional batch processing systems that delay data availability and insights. Competitors are rapidly adopting real-time analytics to enhance their financial operations, making it imperative to catch up.

Unique Selling Proposition

Our solution offers a unique combination of real-time data processing and a data mesh architecture, ensuring superior data quality, observability, and scalability, tailored for the specific needs of the banking sector.

📈Customer Acquisition Strategy

Our strategy includes leveraging industry partnerships, targeted marketing campaigns, and showcasing successful case studies to demonstrate the transformative power of real-time financial analytics in improving operational efficiency and compliance.

Project Stats

Posted:July 21, 2025
Budget:$50,000 - $150,000
Timeline:16-24 weeks
Priority:Medium Priority
👁️Views:18414
💬Quotes:757

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