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Hinshaw & Culbertson LLP

Lead Data Engineer

Hinshaw & Culbertson LLP

Lead Data Engineer building Azure data platforms for Hinshaw & Culbertson, a national law firm. Owning pipelines, warehouse architecture, governance, and production data operations.

Posted 8/5/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $140,000 - $180,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining ETL/ELT pipelines and cloud-based data platforms, particularly within Microsoft Azure. Proficient in data architecture standards, data quality management, and translating technical concepts for diverse audiences.

Highest-signal resume keywords
ETL/ELT DevelopmentAzure Data FactoryData Warehouse ArchitectureMS SQL SkillsData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data IntegrationRelational Database DesignPerformance TuningScripting in PythonPowerShellC#/.NETData Quality ControlsData CatalogingMonitoring and AlertingCI/CD Pipelines
Soft Skills
Excellent Communication SkillsProfessionalismProblem-Solving
Tools & Technologies
Azure DatabricksAzure Data Lake StorageAzure Synapse AnalyticsPower BITableauGitTalendBoomi
Certifications & Qualifications
Microsoft Certified: Azure Data Engineer Associate
Industry Keywords
Data GovernanceData QualityData LineageEnterprise Data WarehouseLakehouse ArchitectureProduction Data WorkflowsInformation GovernanceConfidentiality Requirements

Tech Stack

Tools & technologies
AzureCloudETL.NETPythonSQLTableau

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • 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

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