Data Engineer

Manatt Phelps & Phillips•Boston, NY

1d•Hybrid

About The Position

Manatt, Phelps & Phillips, LLP is seeking a Mid-Level Data Engineer with SQL Server Administration (DBA) experience. The role is responsible for ELT processes that move critical data across Customer (CRM), Finance (ERP), Billing, and Legal ecosystems. Reporting to the Data Architect, the Data Engineer will design, build, test, and maintain scalable data pipelines and solutions in accordance with established frameworks, architectural standards, and data governance practices. The position also ensures the health, security, and performance of enterprise Microsoft SQL Server environments, working closely with business applications, Infrastructure, and Security teams to maintain high availability, performance, and robust disaster recovery. Data movement, storage, and processing must adhere to client ethical walls, encryption standards, and row- and column-level access controls required in a professional services environment. The workplace schedule is hybrid: three days on-site each week and two days remote. The employee must be willing to provide on-call support outside standard business hours for critical technical issues. The stated base annual pay range is $160,000–$190,000, with the actual offer depending on skills, qualifications, experience, location, and internal equity. A range of medical, financial, and/or other benefits dependent on the position will also be offered.

Requirements

Five years of hands-on experience in data engineering, data warehousing, and SQL Server database administration.
Experience interpreting and working with business application data across Customer, Finance, Billing, and Legal systems.
Strong architectural mindset that treats security and compliance as foundational design requirements.
Hands-on SQL Server administration experience, including query profiling, indexing strategies, execution plan analysis, and database maintenance.
Experience installing, configuring, patching, upgrading, and maintaining Microsoft SQL Server environments.
Direct experience building ETL/ELT pipelines using Azure Data Factory (ADF) or comparable data integration platforms.
Hands-on experience developing Lakehouse and Data Warehouse solutions within the Microsoft Fabric ecosystem.
Advanced proficiency developing and troubleshooting complex T-SQL scripts, stored procedures, functions, and triggers.
Experience with Git, Azure DevOps, and pipeline deployment processes.
Proficiency in Python or PySpark for cloud-based data transformation and processing.
Willingness to work on-site three days per week and remotely two days per week.
Willingness to be available outside standard business hours to troubleshoot and resolve critical technical issues as needed.

Nice To Haves

Experience working with regulated data in Legal, Tax, Finance, or Healthcare environments.
Familiarity with Fabric CI/CD, deployment pipelines, GitHub integration, data modeling, Power BI semantic models, and Fabric capacity and cost monitoring.
Microsoft Certified: Fabric Data Engineer Associate (DP-700) certification.
Microsoft Certified: Azure Data Engineer Associate (DP-203) certification.
Microsoft Certified: Administering Relational Databases (DP-300) certification.

Responsibilities

Design, develop, and implement data integration pipelines using standard and custom connectors.
Design, build, and deploy end-to-end Microsoft Fabric solutions, including Lakehouse, Data Warehouse, and semantic layer architectures.
Ensure data movement, storage, and processing comply with client ethical walls, encryption standards, and row- and column-level access controls.
Develop production-grade data transformation logic using T-SQL, Python, and PySpark in cloud notebooks and stored procedures.
Monitor SQL Server database health, optimize indexing, tune slow-running queries, and manage transactional replication, backup and recovery strategies, and user permissions.
Design and manage SQL Server high-availability and disaster-recovery architectures, including Always-On Availability Groups, Failover Clustering, Log Shipping, and Replication.
Monitor system performance and optimize queries using execution plans, indexing strategies, statistics, and bottleneck analysis.
Manage user access, audit permissions, enforce role-based security, and implement data encryption standards.
Schedule, test, and maintain full, differential, and transaction log backups.
Implement automated data validation, error handling, alerting, and performance monitoring across SQL Server and Microsoft Fabric environments.