Lead Data Engineer

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Hinshaw & Culbertson LLP

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1934

⚖️ Legal

🛡️ Insurance

🏥 Healthcare

Legal • Insurance • Healthcare

Hinshaw & Culbertson LLP is a national law firm that provides litigation, business advisory, and regulatory compliance services to clients across the United States. The firm publishes frequent insights, alerts, webinars and press releases on topics such as insurance law, healthcare compliance, antitrust, and AI-related business interruption risk, and maintains multiple offices and leadership, diversity, and pro bono initiatives. Hinshaw serves clients in leading industries with legal representation and advisory work, and highlights practices and hires in insurance and healthcare among other areas.

📋 Description

• Design, build, and maintain ETL/ELT pipelines integrating finance, HR, CRM, document management, and other enterprise systems • Define and enforce data architecture standards, models, schemas, and storage patterns for cloud data warehouse and lakehouse platforms • Lead implementation and operation of Azure Data Factory, Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics • Own enterprise data warehouse and lakehouse platforms, including models, ingestion pipelines, performance, reliability, and operational health • Implement source control, branching, CI/CD, automated testing, deployment workflows, monitoring, and alerting • Oversee scheduling, execution, reconciliation, and monitoring of production data workflows • Identify and resolve data pipeline failures, data quality issues, and performance bottlenecks • Partner with Information Governance and Security teams on data quality, lineage, reconciliation, stewardship, and source-of-truth ownership • Translate stakeholder requirements into technical solutions and explain data concepts to non-technical audiences • Ensure data solutions comply with security policies, confidentiality requirements, and regulatory obligations • Evaluate emerging data, analytics, and AI capabilities and lead proof-of-concepts • Provide design guidance, code reviews, and technical coaching to junior engineers or database professionals • Lead data projects from initiation through delivery, coordinating internal teams and external vendors or consultants • Ensure knowledge transfer and long-term sustainability

🎯 Requirements

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience • 8+ years of hands-on experience in data engineering, ETL/ELT development, and data integration • 3+ years of experience designing and operating cloud-based data platforms, with Microsoft Azure preferred • Strong MS SQL skills and experience with relational database design, development, and performance tuning; SQL Server preferred • Experience building reliable production data pipelines with monitoring, alerting, and reconciliation • Experience with source control and deployment practices for data workflows, including Git and CI/CD pipelines • Excellent written and verbal communication skills, including explaining technical concepts to non-technical audiences • Ability to handle sensitive and confidential information with discretion and professionalism • Availability for occasional after-hours work for major releases or production incidents • Advanced experience with ADLS, Databricks, Azure Data Factory, and Synapse preferred • Experience implementing enterprise data warehouses, data marts, and lakehouse architectures preferred • Experience with Azure Data Factory, Talend, Boomi, or similar data integration platforms preferred • Strong scripting and programming skills in Python, PowerShell, and/or .NET/C# preferred • Familiarity with Power BI or Tableau preferred • Experience with data governance, data quality controls, data cataloging, and lineage documentation preferred • Law firm or professional services experience is a plus • Relevant certifications, such as Microsoft Certified: Azure Data Engineer Associate, are a plus

🏖️ Benefits

• Competitive compensation • Comprehensive benefits program • Opportunities to work on enterprise-scale technology initiatives • Reasonable accommodations to qualified individuals with disabilities