Lead Legal Data Engineer – AI & Automation

Greenberg Traurig, LLP; Orlando (FL); On-site; USD 140,000 - 190,000; Full time

Job summary

Greenberg Traurig, LLP is seeking a Legal Data Engineer Lead to design, build, and maintain AI-enabled data solutions supporting legal matters and client engagements across U.S. offices. This role blends complex data workflows, automation, and AI to deliver scalable, high-quality outputs.

The position requires strong Python and SQL skills, experience in data analytics, and a commitment to responsible AI and quality control within a professional services environment.

Qualifications

• Bachelor's degree in a quantitative field required.
• Minimum 5 years in data engineering, analytics, or related technical discipline.
• Experience incorporating AI, generative AI, ML, or NLP into data workflows.
• Proficiency in Python and SQL for data processing and automation.
• Ability to validate AI outputs and ensure reliability and accuracy.
• Experience in legal or professional services environments preferred.

Responsibilities

• Designs, develops, tests, and maintains complex data workflows and AI-enabled processing techniques.
• Develops Python-based data processing, extraction, transformation, and reporting solutions.
• Designs AI workflows to extract, classify, summarize, and structure information from documents and data sources.
• Implements validation logic, QA procedures, and human-in-the-loop reviews.
• Collaborates with attorneys and technical teams to translate requirements into data solutions.
• Provides technical guidance and mentorship to junior staff.

Skills

Python

Data analysis

Problem solving

Attention to detail

Communication

Team collaboration

AI concepts

Quality assurance

Education

Bachelor's degree in Data Analytics or related field

Tools

SQL Server

Python

Excel

REST APIs

JSON

Git

Azure

Power BI

Job description

Greenberg Traurig, LLP is seeking a Legal Data Engineer Lead to design, build, and maintain AI-enabled data solutions supporting legal matters and client engagements across U.S. offices. This role blends complex data workflows, automation, and AI to deliver scalable, high-quality outputs.

The position requires strong Python and SQL skills, experience in data analytics, and a commitment to responsible AI and quality control within a professional services environment.