Principal Data Analyst

Superior Court of California County of Los Angeles•Los Angeles, CA

40d•Hybrid

About The Position

The Superior Court of Los Angeles County is the largest unified trial court in the United States. The Court's 582 judicial officers and its dedicated workforce of over 4,600 full-time employees serving across 36 facilities work purposefully and seamlessly to achieve the mission to provide equal access to justice to all of Los Angeles County. At the heart of the Los Angeles Superior Court is commitment and collaboration between team members who contribute professional skill sets and meaningful work experiences toward the goal of serving the community at large. Accessible career paths, a healthy work-life balance, job stability, and comprehensive total rewards including generous pay and benefits, a robust public sector pension, and Court matched 401K/457 individual savings plans, are just some of the values that the Court offers to every member of its thriving workforce. Plan your future with the Los Angeles Superior Court - connect with us today. ABOUT THE POSITION We're looking for a passionate Principal Data Analyst who is eager to design, build, and implement modern analytics solutions. The ideal candidate will play a key role in designing and engineering state-of-the-art data analytics solutions, leveraging Power BI, tools like WhereScape RED, ADF, Snowflake and advanced analytics using AI and ML technologies to drive innovation and efficiency. With proven experience implementing comprehensive systems using automation frameworks and cloud data platforms, this role offers the opportunity to further expand your expertise in advanced data engineering and analytical solutions while contributing to transformative initiatives. The official classification for this position is Business Systems Analyst, Principal. For a detailed job description, click here. Please note the requirements in the job description may vary from the requirements in this bulletin. Applicants must meet the requirements stated in this bulletin. THIS IS A TELEWORK ELIGIBLE OPPORTUNITY This position may be eligible for full or partial telework following an initial training period and contingent upon the needs of the Court.

Requirements

OPTION I: 9+ years' experience in business analysis, requirements definition and information technology support as it relates to data and analytics.
OPTION II: Associate's degree in information technology, computer science, management information systems, or related field; -AND- 7+ years' experience in business analysis, requirements definition and information technology support as it relates to data and analytics.
OPTION II: Bachelor's degree in information technology, computer science, management information systems, or related field; -AND- 5+ years' experience in business analysis, requirements definition and information technology support as it relates to data and analytics.
OPTION IV: Master's degree in information technology, computer science, management information systems, or related field; -AND- 3+ years' experience in business analysis, requirements definition and information technology support as it relates to data and analytics.

Nice To Haves

Experience in design, development, and deployment of data analytics solutions to support data driven decision-making.
Proficient in one or more analytics platforms and tools. Deep understanding of data architecture, including data warehousing principles and best practices.
Strong experience with Power BI, including report and dashboard creation, data modeling, and DAX.
Experience with Snowflake, Azure, and exposure to advanced data engineering tools.
Proficient with automation tools like WhereScape RED, Azure Data Factory.
Understanding of data modeling concepts and experience in building effective data models.
Ability to write SQL queries for data extraction, transformation, and manipulation. Advanced skills in SQL development and optimization across Microsoft SQL Server, SSRS, PBI Report Server and Oracle environments.
Experience documenting business processes and the ability to translate business requirements into technical solutions.
Exposure to programming languages such as Python or R, especially in the context of analytics.
Familiarity with AI and machine learning concepts and their application in predictive analytics projects.
Familiarity with DevOps/Data Ops practices.

Responsibilities

Analytics Implementation: Design and execute end-to-end data analysis projects using advanced analytics tools and techniques to derive actionable insights and support strategic decision-making.
Data Engineering: Contribute to the design and optimization of scalable, reliable data storage and processing solutions. Apply deep understanding of data architecture and warehousing concepts to support enterprise data ecosystems.
Data Visualization & Reporting: Build interactive dashboards and reports using Power BI to communicate data-driven insights effectively. Ensure visual outputs are intuitive, accurate, and aligned with stakeholder needs
Cloud & Automation Tools: Implement data solutions using modern platforms like Snowflake and Azure. Use automation tools such as WhereScape RED, ADF to streamline data workflows and improve operational efficiency.
Dimensional Modeling: Develop and maintain dimensional data models to enable efficient querying and robust reporting. Ensure models align with business processes and analytical requirements.
SQL Development & Optimization: Write, test, and optimize complex SQL queries across platforms including Microsoft SQL Server, SQL Server Reporting Server, PBI Report Server, and Oracle. Enhance data retrieval performance and maintain query efficiency at scale.
Project Execution & Collaboration: Lead the technical delivery of data-related initiatives, managing tasks, timelines, and deliverables within cross-functional teams. Apply structured methodologies to ensure successful execution.
Technical Mentorship & Best Practices: Serve as a subject matter expert and resource to peers by sharing knowledge, providing technical guidance, and promoting best practices in analytics development and data management.