Data Integration Engineer

Litera

82d • $115,000 - $145,000

About The Position

Join the Legal Tech Revolution at Litera. Are you ready to shape the future of how law is practiced? At Litera, we're leading the legal AI revolution. As pioneers at the forefront of legal technology, we're transforming how 2M+ legal professionals work every day at the world's top law firms and corporate legal departments through our cutting-edge, AI-driven portfolio of tools. From intelligent document drafting to predictive analytics, from automated workflows to advanced security governance, we deliver innovative solutions seamlessly within Microsoft 365 and across every device lawyers use. With 30+ years of relentless innovation and the majority of the world's largest law firms as our clients, we're just getting started. If you're passionate about building AI-forward solutions that scale globally and want your work to impact millions of legal professionals worldwide, this is your opportunity to be part of something extraordinary—help us continue revolutionizing legal technology and defining what's possible in the legal industry. As part of our strategic growth and commitment to fostering collaboration and operational excellence, we are transitioning to a hybrid working model across North America. We are establishing offices in Austin, Boston, Chicago, Denver, New York City, Philadelphia, New Jersey, Raleigh, and Toronto to serve as key operational hubs, and we are actively seeking talented individuals to join our team in this exciting new phase. This position is located in our Denver office. Candidates should reside within reasonable commuting distance, as this role requires on-site presence at least three days per week. This hybrid approach enables us to build a collaborative and innovative work environment while maintaining the flexibility that supports both productivity and work-life balance.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 5+ years of experience in data integration or data engineering, preferably in legal tech or regulated industries.
• Strong proficiency in SQL, Python, and data modeling.
• Experience with cloud platforms (Azure, AWS, or GCP) and tools like Databricks, Airflow, or Azure Data Factory.
• Experience with Snowflake, Rivery, dbt preferred.
• Experience with Azure Data Factory preferred.
• Familiarity with legal data systems such as iManage, NetDocuments, Aderant, or Elite 3E.
• Understanding of Gen AI concepts including LLMs, RAG (Retrieval-Augmented Generation), and vector databases.

Nice To Haves

• Experience with data architectures and semantic data modeling.
• Knowledge of MLOps practices and tools like MLflow.
• Exposure to data privacy and anonymization techniques in legal contexts.
• Familiarity with BI tools (e.g., Power BI, Tableau) for legal analytics.
• Strong communication skills and ability to work cross-functionally in a fast-paced environment.

Responsibilities

• Design and implement data pipelines for ingesting, transforming, and integrating legal data from diverse sources (e.g., case law databases, contract repositories, legal management systems).
• Collaborate with AI/ML teams to prepare and optimize datasets for training and deploying Gen AI models.
• Develop and maintain ETL/ELT workflows using modern data engineering tools and cloud platforms.
• Ensure data quality, governance, and compliance with legal and ethical standards.
• Build and integrate with APIs and services to expose integrated data to downstream applications and analytics platforms.
• Work with legal domain experts to map and model data for semantic understanding and contextual relevance.
• Monitor and troubleshoot data pipelines to ensure performance, scalability, and reliability.

Benefits

• Comprehensive benefits package including health insurance and retirement savings plans.
• Generous paid time off.
• Supportive work-life balance.
• Career paths and opportunities for professional development.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Bachelor's degree
• Number of Employees: 501-1,000 employees