DescriptionWhat You Will Do: 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.
Key Responsibilities:- 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, InterAction, 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 DevOps to promote changes across development, test, and production workspaces.
- 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.
Essential Job Requirements:- 3-5+ years of hands-on ETL/ELT or data engineering experience building and supporting production data pipelines.
- Microsoft Fabric experience is preferred but not required; equivalent experience with Azure Data Factory, Synapse Analytics, Databricks, SSIS, dbt, or other modern ETL frameworks will be considered.
- Working knowledge of medallion architecture (bronze/silver/gold), lakehouse and data warehouse concepts, and dimensional modeling.
- Strong T-SQL skills, with proven hands-on experience in MS SQL Server including query optimization and performance tuning.
- Proficiency in Python and PySpark, or a demonstrated ability to ramp up quickly on Spark-based transformation.
- Experience with incremental load, change data capture, and slowly changing dimension patterns.
- Experience ingesting data from REST APIs, JSON and XML payloads, flat files, SFTP sources, and direct database connections.
- Rigorous approach to data quality, including validation, reconciliation, and alerting.
- Familiarity with source control (Git) and CI/CD practices for data artifacts.
- Experience building, maintaining, and supporting analytics models for reporting.
- Power BI development experience a plus, including semantic models, DAX, and report delivery.
- Ability to deliver high-quality work quickly in a fast-paced, deadline-driven environment, with a track record of managing competing priorities effectively.
- Willingness to adopt AI-assisted development tooling as part of a regular engineering workflow.
Skills, Knowledge and Abilities:- Bachelor's degree in Computer Science, Information Systems, Data Analytics, or a related field, or equivalent practical experience of 5+ years in data engineering.
- Data Platform: Microsoft Fabric (Lakehouse, Warehouse, OneLake, Data Factory pipelines, Dataflows Gen2, Notebooks, Direct Lake), Azure Data Factory, Synapse, Databricks.
- Languages: T-SQL, Python, PySpark, Spark SQL; KQL a plus.
- Architecture: medallion architecture, dimensional modeling and star schemas, slowly changing dimensions, Delta Lake and Parquet formats, partitioning.
- Integration: REST APIs, JSON, XML, flat file and SFTP ingestion, ODBC/JDBC, OAuth 2.0, change data capture.
- BI and Semantic Layer: Power BI, semantic models, DAX, row-level security.
- Cloud and Security: Microsoft Azure, Entra ID, Key Vault, Microsoft Purview, data sensitivity labeling and classification.
- Tools and DevOps: Git, Fabric Git integration and deployment pipelines, Azure DevOps, VS Code, SQL Server Management Studio.
- AI Development: Claude Code, GitHub Copilot, or equivalent AI-assisted tooling a plus.
- Legal data standards: SALI/LMSS taxonomy experience a plus.
- Law firm data experience (Aderant, Intapp, iManage, InterAction, Dayforce) a plus.
- Strong analytical and problem-solving skills with excellent attention to detail.
- Exceptional communication skills, with the ability to translate technical concepts for non-technical stakeholders.
- Proven ability to work both independently and collaboratively in a team-oriented environment.
- A continuous learner who actively tracks and experiments with emerging tools, especially in the data and AI space.
Office Location: Roseland, New Jersey (Hybrid)
Schedule: Full-Time, Monday through Friday, 9:00 AM - 5:00 PM
Amount of Travel Required: None
The expected salary range for candidates meeting the requirements of this position is $125,000 to $140,000. The range provided is the salary that Lowenstein Sandler in good faith believes at the time of this posting that it is willing to pay for the advertised position. Exact compensation will be determined based on individual candidate qualifications and location. Our benefits package includes coverage options for medical, dental, vision, prescription drug, life insurance, disability, FSAs, 401K, and paid time off.
Disclaimers:This job description is not designed to cover or contain a comprehensive listing of all activities, duties, or responsibilities required by employee.
Lowenstein Sandler LLP is not accepting resumes from search firms for this position. Regardless of past practice, all resumes submitted by search firms are to be deemed the sole property of Lowenstein Sandler LLP, and no fee will be paid in the event the candidate is hired by Lowenstein Sandler LLP as a result of the referral.
