Job Description
Position Overview
The Lead Data Analyst plays a critical role in designing, implementing, and optimizing advanced data analytics solutions to support strategic and operational decision-making. This role partners closely with business, technology, and leadership teams to translate complex data into actionable insights. The position requires strong technical expertise, analytical thinking, and the ability to lead by influence while remaining hands-on with data architecture, analytics, and reporting solutions.
This role is hands-on and requires close collaboration with business and technology teams. The Lead Data Analyst is expected to balance strategic thinking with detailed execution, contribute to architectural decisions, and ensure analytics solutions align with enterprise standards and long-term business objectives.
Key Responsibilities
• Design, develop, and maintain scalable data analytics solutions using Azure Databricks and related enterprise platforms.
• Lead data compilation, transformation, integration, and validation from multiple structured and unstructured data sources.
• Apply advanced statistical, quantitative, and analytical techniques to identify trends, patterns, and opportunities.
• Develop dashboards, reports, and analytical models using Power BI and Databricks AI/BI dashboards.
• Define and implement data standards, best practices, and governance processes to ensure data quality and consistency.
• Collaborate with cross-functional stakeholders to gather requirements and translate business needs into technical solutions.
• Establish processes for monitoring, tracking, and trending data across systems and applications.
• Provide peer review and technical guidance on analytics, programming logic, and data modeling.
• Support leadership and team members with ad-hoc analysis and strategic insights.
• Communicate findings clearly to technical and non-technical audiences.
Technical Skills and Expertise
• Experience with Azure Databricks, Power BI, GitHub, DevOps, and CI/CD pipelines.
• Proficiency in PySpark, Python, SQL, and Scala for data engineering, automation, and analytics.
• Expertise in data modeling, data mapping, and large-scale data processing.
• Experience developing enterprise-grade dashboards and reporting solutions.
• Knowledge of cloud-based data architectures and modern analytics platforms.
Business and Domain Knowledge
• Strong understanding of healthcare data domains, data mapping, and regulatory considerations.
• Ability to translate business problems into data-driven solutions.
• Experience working with stakeholders across multiple organizational levels.
Education and Experience Requirements
• Bachelor’s degree preferred.
• 7–9 years of progressive experience in data analytics, data engineering, or related roles.
• Demonstrated experience delivering analytics solutions from concept through production.
Preferred Qualifications
• Experience working in large enterprise data environments.
• Familiarity with healthcare analytics and reporting standards.
• Strong problem-solving skills and attention to detail.
• Excellent written and verbal communication skills.
To all current Molina employees: If you are interested in applying for this position, please apply through the Internal Job Board.
Molina Healthcare offers a competitive benefits and compensation package. Molina Healthcare is an Equal Opportunity Employer (EOE) M/F/D/V.
Similar Jobs
.png)
What you need to know about the Los Angeles Tech Scene
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
