Data Engineer- NLP, Python, LLM (4-6 years experience)

Job Title: Data Engineer

Role Overview

We are seeking a detail-oriented Data Engineer with strong expertise in Python, Natural Language Processing (NLP), and LLM-assisted analytics to support large-scale contract text analysis. This role focuses on structured extraction, pattern discovery, and analytics-driven insights from redlined legal documents.

This is a data and analytics role not a legal drafting or negotiation function.

Essential Functions

Redline Pattern Extraction & Variant Discovery

• Analyze historical tracked changes and document markups at scale to identify recurring edit patterns, counterparty tendencies, and structured clause-variation clusters within legal text.
• Group similar edits into normalized variant sets without determining legal fallback positions or acceptability.

Clause Change Clustering & Exception Mapping

• Classify edits by frequency, type (add / delete / narrow / broaden), and document location.
• Surface anomalies and outliers for review by legal SMEs (no interpretation required).

LLM-Assisted Summarization & Tagging

• Leverage AI tools and LLM frameworks to accelerate classification of edit intent and thematic categorization, with structured QC oversight.
• Generate structured outputs to support SME review (no drafting or position-setting responsibilities).

Insight Packaging for SMEs & Playbook Authors

• Produce clean variant summaries, clause drift reports, and exception trend snapshots.
• Deliver contract-type-specific insight packs (e.g., across 200500 agreements) highlighting recurring edits, variant clusters, and trend deviations.
• Present structured findings to legal stakeholders for final determination.

Scalable Text Extraction & Data Normalization

• Develop and operate Python-based scripts and approved AI services for large-scale text extraction, normalization, and clustering.
• Extract and compare previous vs. revised language across batches of Word documents.
• Treat redlines as structured text elements rather than legal judgments.

Secondary Analytics (As Bandwidth Allows)

• Support adjacent analytics initiatives such as help-desk pattern identification, matter trend clustering, and metadata normalization.
• Strictly analytical scope no contract drafting, negotiation, or rule design.

Cross-Time-Zone Collaboration

• Provide clear asynchronous updates, maintain backlog transparency, and communicate structured pattern insights to US-based stakeholders.

Required Skills & Technical Expertise

• Strong proficiency in Python (text parsing, data manipulation, automation).
• Experience with NLP techniques (tokenization, clustering, semantic similarity, embeddings).
• Exposure to LLM-assisted workflows for classification and summarization.
• Experience handling large volumes of unstructured or semi-structured documents.
• Familiarity with Word document parsing (e.g., tracked changes, redlines) preferred.
• Strong data structuring, normalization, and analytical reasoning skills.

Education & Experience

• Bachelors degree (B.Tech / B.E / B.Sc / B.Com / BA / LL.B).
• 47 years of experience in data or document analytics.
• Experience working with structured/unstructured text datasets required.
• Exposure to legal document formats preferred (not mandatory).
• Postgraduate qualification in Analytics, Data Science, or Legal Operations is a plus.
• Experience working with global teams across time zones preferred.