Lead Data Engineer
| Company | The State Bar of California |
|---|---|
| Location | San Francisco, CA, USA |
| Salary | $112497 – $149972 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- Experience in building scalable, cloud-based data solutions
- Strong understanding of modern data architectures, data integration patterns, and secure design principles
- Demonstrated success in leading cross-functional collaboration
- Clear understanding of compliance standards (e.g., PII, PCI, HIPAA, CPRA)
- Microsoft certification in one or more of the following is strongly desired: Azure Data Engineer Associate; Power BI Data Analyst Associate; Azure Solutions Architect Expert; or any other data analysis-related certifications
- Bachelor’s degree in computer science or a closely related field that develops skills related to the essential duties, or equivalent academic achievement
- Five (5) years of experience at the advanced journey-level in the information systems field including system analysis, business process design, development and implementation of business application solutions or IT project management, of which at least one (1) year was in a lead capacity
Responsibilities
- Lead the design, development, and maintenance of scalable data pipelines using Azure Data Factory, Synapse Analytics, and Data Lake Storage to ingest, transform, and publish structured and unstructured data
- Drive the automation of end-to-end and event-driven workflows using Azure Logic Apps, ensuring real-time or scheduled data synchronization and integration with external systems
- Direct enterprise-level data modeling and transformation efforts to support reporting, dashboards, and analytics, including validation and quality checks to ensure consistency and reliability
- Guide and collaborate with IT and business teams to gather data requirements, define transformation logic, and develop shared documentation such as the data dictionaries
- Develop and oversee enhancements of the Azure-based data architecture, focusing on scalability, reusability, and long-term maintainability
- Establish and implement data governance standards, including metadata management, lineage tracking, and data privacy and security controls aligned with organizational compliance needs
- Optimize datasets for Power BI and promote self-service analytics through clean, reusable data models and standardized practices
- Manage, monitor, troubleshoot, and tune pipeline performance, proactively resolving issues and establishing observability standards for operational reliability
- Ensure comprehensive documentation and lead knowledge transfer efforts to support long-term IT business and user sustainability and system adoption
- Maintain and support databases for custom and legacy applications, including performance tuning, backup and recovery, indexing, and monitoring
- Spearhead the optimization of stored procedures, ETL jobs, and scheduled tasks, ensuring efficiency and reliability across both modern and legacy environments
- Partner with application teams to troubleshoot and resolve data-related issues, implement fixes, and ensure data integrity in legacy platforms
- Lead enterprise data migration efforts aligning strategies for access control, security, and compliance as data moves from legacy to modern platforms
- Build and maintain an enterprise data dictionary and catalog to improve data discoverability and consistency across the organization
- Lead and implement data security and compliance standards, across the Bar’s data footprint
Preferred Qualifications
- Proficient in building scalable data pipelines using Azure Data Factory, Synapse Analytics, Azure Data Lake, and Logic Apps
- Strong SQL skills with experience in data transformation, validation, and optimization for reporting and analytics
- Skilled in dimensional modeling and modern data platform design to support dashboarding and analytical use cases
- Familiar with data quality frameworks, including validation, anomaly detection, and exception handling processes
- Experience with metadata management, data cataloging, and governance tools such as Azure Purview (or equivalents)
- Familiarity with CI/CD practices and version control systems such as Git
- Demonstrated ability to translate business needs into technical requirements and collaborate effectively across IT and business teams
- Strong communication, documentation, and stakeholder engagement skills to support alignment and knowledge sharing
- Data engineering languages such as Python
- Knowledge of data security best practices including encryption, data masking
- Familiarity with data visualization tool Power BI