Data Engineer

Lowenstein Sandler is a one of the most sophisticated law firms in the United States, with over 400 lawyers and 300 business services professionals serving clients from offices in New York, Palo Alto, Roseland, Salt Lake City, San Francisco, Washington, D.C., and Wilmington. We recruit candidates who seek a collaborative, entrepreneurial culture that prioritizes our clients, our colleagues, and the communities where we work and live.

Committed to career development and to an inclusive workplace, the firm offers many programs and opportunities for personal and professional growth. We seek professionals for our business services group who share these values.

The Data Engineer plays a central role within the Software Engineering team, responsible for building and maintaining the data pipelines that feed the firm's Microsoft Fabric Data Lakehouse. Working closely with the Data Architect, this role ingests, transforms, and curates data from the firm's core business systems through a medallion architecture to deliver trusted, analytics-ready datasets that power reporting, business intelligence, and AI-driven applications across the firm.

This role requires an engineer who thrives in a fast-paced environment, is rigorous about data quality and governance, and actively integrates AI tooling into their development workflow.

• Design, build, test, and maintain ETL/ELT pipelines that ingest data from the firm's enterprise systems into the Microsoft Fabric Data Lakehouse, using Data Factory pipelines, and Spark notebooks.
• Implement and maintain the bronze, silver, and gold layers of the firm's medallion architecture, covering raw ingestion, cleansing and conformance, and curated analytics-ready models.
• Partner with the Data Architect to translate logical data models into physical implementations, including star schemas, slowly changing dimensions, and Power BI semantic models in the gold layer.
• Build and maintain source-system integrations across Aderant Expert, Intapp, iManage, Inter Action, Dayforce, SharePoint Online, and third-party APIs, applying incremental load and change data capture patterns and normalizing key entities to the SALI/LMSS taxonomy.
• Develop transformation logic in T-SQL, Spark SQL, and PySpark, with built-in data quality validation, reconciliation to source, exception handling, and alerting.
• Diagnose and trace data discrepancies end-to-end — from source system through bronze, silver, and gold layers to the final DAX measure or report — identifying and resolving root causes.
• Monitor, tune, and optimize pipeline performance, refresh windows, and Fabric capacity consumption to control cost and meet business service levels.
• Implement data governance and security controls with the Data Architect and Information Security, including workspace permissions, row-level security, sensitivity labeling, and law firm confidentiality and ethical wall requirements.
• Partner with Finance, Marketing, Human Resources, practice groups, and IT stakeholders to gather requirements, and support business intelligence developers and self-service users with reliable, well-modeled, documented datasets.
• Manage data artifacts through source control and deployment pipelines, using Fabric Git integration and Azure Dev Ops to promote changes across development, test, and production work spaces.
• Leverage Claude Code and other AI-powered development tools to accelerate pipeline development, testing, and documentation, and build the curated datasets that power the firm's AI and agentic applications.
• Maintain data dictionaries, lineage, and operational runbooks, and provide production support and escalation-level troubleshooting for failed or degraded data loads.