Legal Data Engineer Lead

Greenberg Traurig (GT), a global law firm with locations across the world in 15 countries, has an exciting employment opportunity for you. We offer competitive compensation and an excellent benefits package, along with the opportunity to work within an innovative and collaborative environment.

We are seeking a highly skilled professional who thrives in a fast-paced, deadline-driven environment. The ideal candidate possesses strong problem-solving and decision-making abilities, ensuring efficiency and accuracy in every task. With a dedicated work ethic and a can-do attitude, you will take initiative and approach challenges with confidence and resilience. Excellent communication skills are essential for collaborating effectively across teams and delivering exceptional client service.

If you are someone who demonstrates initiatives, adaptability, and innovation, we invite you to join our team.

The Legal Data Engineer Lead is responsible for designing, developing, and maintaining data-driven and AI-enabled solutions that support legal matters, client engagements, and internal business initiatives. This role oversees complex data engineering, integration, automation, analytics, and AI projects involving large, diverse, and often unstructured data sets, leveraging advanced technical expertise to deliver scalable, defensible, and high-quality solutions. The position exercises independent judgment in selecting appropriate technologies and methodologies, evaluates the accuracy and reliability of AI-assisted outputs, identifies opportunities to enhance workflows through automation and AI, and provides technical guidance to team members.

• Designs, develops, tests, and maintains complex data workflows and pipelines incorporating traditional data engineering, automation, and AI-enabled processing techniques.
• Develops Python-based solutions for data processing, extraction, classification, transformation, validation, reconciliation, and reporting.
• Designs workflows that use generative AI, large language models, multimodal AI, or other AI technologies to extract, classify, summarize, normalize, or structure information from PDFs, documents, images, spreadsheets, and other structured and unstructured data sources.
• Develops structured AI workflows using techniques such as prompt engineering, schema-based outputs, JSON processing, validation logic, exception handling, and automated quality-control procedures.
• Integrates AI capabilities with Python, APIs, databases, cloud services, and traditional data-processing workflows to create repeatable and scalable analytical solutions.
• Evaluates AI-generated outputs for accuracy, completeness, consistency, and reliability and develop validation procedures appropriate for legal and client-facing work.
• Designs human-in-the-loop review processes and other quality-control mechanisms for AI-assisted workflows where appropriate.
• Identifies appropriate and inappropriate use cases for AI based on data sensitivity, analytical risk, accuracy requirements, confidentiality, and the intended use of the resulting work product.
• Assists in developing standards, documentation, and governance practices for the responsible use of AI within Legal Data Analytics workflows.
• Evaluates emerging AI technologies, models, platforms, and development approaches and recommend tools that can improve the efficiency, accuracy, or scalability of the department's analytical services.
• Prototypes and develops AI-enabled tools and self-service applications that automate repetitive data preparation, extraction, review, or analytical processes.
• Collaborates with attorneys and technical professionals to translate legal and business requirements into data engineering and AI-assisted analytical solutions.
• Provides technical guidance to team members on data extraction, transformation, automation, reporting, data validation, and analytics tools and processes.

• Exceptional attention to detail, organizational skills, and commitment to data accuracy and quality assurance.
• Demonstrated collaboration and client service orientation with the ability to partner effectively across departments and business functions.
• Advanced analytical, problem-solving, and critical thinking skills with the ability to work with complex datasets and identify data quality issues, trends, and anomalies.
• Strong Python…