Real-Time Legal Data Engineering Platform Development

As a leading enterprise within the legal services industry, we recognize the critical importance of efficient data management and processing to maintain our competitive edge. Our current data infrastructure struggles with latency issues and lacks the real-time insights necessary to adapt to the fast-paced legal environment. This project proposes the development of a robust data engineering platform that leverages real-time analytics and data observability. By implementing a data mesh architecture, we aim to decentralize data ownership and improve data quality across departments. Technologies such as Apache Kafka will facilitate event streaming, allowing us to process and analyze data in real-time. Integrating Spark and Airflow will automate and optimize data workflows, providing seamless data integration and transformation. We will also deploy dbt for data modeling and Snowflake or BigQuery for scalable data warehousing. The platform will enable our legal teams to access timely insights, support strategic decision-making, and enhance our service offerings to clients. With a budget of $50,000 to $150,000, we anticipate the project to be completed within 16-24 weeks, with a medium urgency level.