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Manager Data Analyst Jobs in Rialto, CA (NOW HIRING)

Data Scientist II

Rancho Cucamonga, CA · On-site

$118.60 - $157.14/hr

Under the direction of the Manager, Data Science, the Data Scientist II is responsible for modeling ... Minimum of four (4) years of experience in analytics, data science, and business intelligence

Business Operations Analyst

Orange, CA · On-site +1

$85K - $100K/yr

... management, data analytics, contract administration, compliance initiatives, and strategic operational support. This role partners closely with operational leadership to identify business needs ...

... data management and decision-making capabilities. Qualifications : Required : • Minimum of four ... analysis and critical thinking skills • Excellent communication and interpersonal skills • ...

The Temporary Sales Systems Analyst plays a key support role between the National and Regional ... Leverage Excel to manage data files, track updates, and support reporting needs. * Ensure accurate ...

... Analytics. Responsibilities * Build, test, and deploy ETL/ELT patterns in an efficient, organized manner * Own data acquisition, transformation, modeling, and lineage * Manage data pipelines using ...

Showing results 41-60

Manager Data Analyst information

See Rialto, CA salary details

$34.1K

$82.9K

$136.4K

How much do manager data analyst jobs pay per year?

As of Aug 11, 2026, the average yearly pay for manager data analyst in Rialto, CA is $82,869.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,700.00 and $97,300.00 per year, depending on experience, location, and employer.

What does a Manager Data Analyst do?

A Manager Data Analyst oversees a team of data analysts, guiding their work in collecting, processing, and interpreting complex data to help organizations make informed decisions. They are responsible for developing data strategies, ensuring data accuracy, and translating analytical findings into actionable insights for business leaders. In addition to technical expertise, they often collaborate with other departments, manage projects, and mentor team members to support business goals and drive growth.

What is the difference between Manager Data Analyst vs Data Analyst?

AspectManager Data AnalystData Analyst
ResponsibilitiesOversees data teams, manages projects, develops strategiesAnalyzes data, prepares reports, supports decision-making
Required SkillsLeadership, project management, advanced analyticsData analysis, SQL, Excel, visualization tools
Experience5+ years, leadership experience often required1-3 years, entry to mid-level
CertificationsRelevant certifications like CAP, PMP beneficialSQL, Excel, Tableau certifications advantageous

The main difference between a Manager Data Analyst and a Data Analyst lies in scope and responsibility. Managers oversee teams and strategic initiatives, while Data Analysts focus on data analysis and reporting. Both roles require strong analytical skills, but managerial positions demand leadership and project management experience.

How does a Manager Data Analyst typically balance hands-on data analysis with overseeing team projects?

A Manager Data Analyst is often responsible for both performing complex data analysis and managing a team of analysts. Balancing these duties involves delegating day-to-day analytical tasks to team members while focusing on project oversight, strategic planning, and stakeholder communication. Managers frequently review team outputs, provide mentorship, and ensure that data-driven insights align with business objectives. This dual role requires strong organizational skills and the ability to shift between technical work and leadership responsibilities.

What are the key skills and qualifications needed to thrive as a Manager Data Analyst?

To thrive as a Manager Data Analyst, you need a strong background in statistics, data modeling, and analytics, often supported by a degree in a quantitative field and experience in data analysis roles. Familiarity with tools such as SQL, Python or R, business intelligence platforms (e.g., Tableau, Power BI), and data management systems is typically required. Leadership, problem-solving abilities, and effective communication skills set standout candidates apart by enabling them to lead teams and translate data insights to stakeholders. These skills are vital for driving data-driven business decisions and ensuring the effective functioning of analytics teams.
What are the most commonly searched types of Data Analyst jobs in Rialto, CA? The most popular types of Data Analyst jobs in Rialto, CA are:
What cities near Rialto, CA are hiring for Manager Data Analyst jobs? Cities near Rialto, CA with the most Manager Data Analyst job openings:
Infographic showing various Manager Data Analyst job openings in Rialto, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 14% Part Time, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $82,869 per year, or $39.8 per hour.

Technical Architect - Data, Analytics & AI

Munich Re

Hesperia, CA • Hybrid

$63.75 - $82/hr

Full-time

Medical, Life, Retirement, PTO

Re-posted 5 days ago


Job description

Location: Princeton, New Jersey Hybrid 40-50% onsite 

Role Overview

We are seeking a Technical Architect (TA) with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.

The Technical Architect will play a critical role in transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.

Technical Architects provide technical leadership across analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.

This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.

The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.

Key Responsibilities

  • Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
  • Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
  • Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
  • Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
  • Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
  • Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
  • Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
  • Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
  • Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
  • Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
  • Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
  • Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
  • Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
  • Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
  • Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
  • Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
  • Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
  • Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions.
  • Establish architectural patterns for AI model deployment, monitoring, versioning, and retraining in cloud environments.
  • Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.

 

Your Profile

  • 4+ years of experience in Enterprise Architecture or Technical Architecture.
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
  • Strong experience with cloud platforms and services, including:
    • Azure (e.g.; Azure AI Studio, Azure Data Services and tools)
    • AWS  (e.g.; Amazon Bedrock, Sagemaker, Data Services and tools)
    • Databricks
  • Handson experience with enterprise data concepts, including:
    • Data Intake and Ingestion
    • Data Warehousing
    • Data Lakes / Lakehouse architectures
    • ETL / ELT
    • Interactive and operational reporting
    • Statistical and regulatory reporting
    • Master Data Management (MDM)
    • Data Governance, Quality, Security, Audit, Balance & Control
  • Solid understanding of enterprise architecture practices, including:
    • Architectural patterns
    • Roadmaps
    • Architecture Review Boards
    • Solution Design Boards
  • Experience defining data management and AI roadmaps, cloudbased services, and reusable architectural patterns.
  • Experience integrating operational data with enterprise data lakes.
  • Strong understanding of data integration challenges and solution patterns.
  • Experience with statistical and data science languages such as Python and R (strong asset).
  • Exposure to AI/ML concepts, including model development, deployment, monitoring, and MLOps (required).
  • Familiarity with Generative AI concepts, AI platforms, and enterprise adoption considerations (strong asset).
  • Strong business acumen with deep understanding of:
    • Financial systems
    • Corporate and backoffice systems
    • Enterprise data management, analytics, and AI technology landscape
  • Strong problemsolving skills, unquestioned integrity, and high collaboration capability.
  • Passion for innovation, continuous improvement, modernization, and change management.
  • Excellent written and verbal communication skills, with the ability to communicate effectively at all levels.
  • High sense of ownership, accountability, and pride in delivered outcomes.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.

The base salary range anticipated for this position is $141,800 - $207,900 plus opportunity for company bonus based upon a percentage of eligible pay.  In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO). 

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range.