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Junior Data Analytics Engineer Jobs in Riverside, CA

A multi-disciplinary architectural, engineering and construction firm is seeking a Junior Engineer ... Analyze data and prepare reports on building envelope performance * Assist in the design of ...

Technical Architect - Data, Analytics & AI

Corona, CA ยท Hybrid

$65.75 - $84.50/hr

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure ... Enterprise data management, analytics, and AI technology landscape * Strong problemsolving skills ...

Data Engineer - Senior Manager

Irvine, CA ยท On-site

$124K - $280K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

Data Engineer

Irvine, CA ยท On-site

$150K - $170K/yr

This role places a strong emphasis on analytics engineering, ensuring that data is not only ingested and processed, but also thoughtfully modeled, curated, and governed to support high-quality ...

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Junior Data Analytics Engineer information

See Riverside, CA salary details

$34.9K

$74.9K

$114.2K

How much do junior data analytics engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for junior data analytics engineer in Riverside, CA is $74,906.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,600.00 and $83,500.00 per year, depending on experience, location, and employer.

What is a Junior Data Analytics Engineer?

A Junior Data Analytics Engineer is an entry-level professional who assists in collecting, processing, and analyzing data to help organizations make informed decisions. They typically work with data pipelines, databases, and analytical tools to support senior data engineers and analysts. Their responsibilities often include cleaning data, writing basic queries, and creating simple reports or dashboards. This role serves as a foundation for more advanced positions in data engineering and analytics.

What are the key skills and qualifications needed to thrive as a Junior Data Analytics Engineer, and why are they important?

To thrive as a Junior Data Analytics Engineer, you need a solid understanding of data analysis, statistics, and programming languages such as Python or SQL, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (e.g., Tableau, Power BI), database management systems, and cloud platforms is commonly expected. Strong problem-solving skills, attention to detail, and effective communication make candidates stand out in this role. These abilities are crucial for accurately analyzing data, translating findings into actionable insights, and enabling data-driven decision-making within organizations.

What are the most common challenges faced by a Junior Data Analytics Engineer when transitioning from academic projects to real-world business data?

One of the most common challenges for Junior Data Analytics Engineers is adapting to the complexities of real-world data, which is often incomplete, inconsistent, or unstructured compared to clean academic datasets. Additionally, there is a stronger emphasis on collaboration with cross-functional teams and communicating findings to non-technical stakeholders. Learning to balance technical analysis with business objectives, and managing multiple tasks or project deadlines, are also typical hurdles. Overcoming these challenges helps junior engineers grow quickly and become valuable contributors to their teams.

What is the difference between Junior Data Analytics Engineer vs Data Analyst?

AspectJunior Data Analytics EngineerData Analyst
Required SkillsBasic programming, data modeling, SQL, data pipeline understandingData visualization, statistical analysis, Excel, SQL
Work EnvironmentCollaborates with data engineers and developers, often in tech or finance sectorsWorks with business teams to interpret data, in various industries
CertificationsSQL, Python, entry-level data certificationsExcel, Tableau, Power BI certifications

Junior Data Analytics Engineers focus on building data pipelines and integrating data systems, requiring programming skills. Data Analysts primarily interpret data through visualization and statistical methods. Both roles often overlap but serve different core functions within data teams.

What are the most commonly searched types of Data Analytics Engineer jobs in Riverside, CA? The most popular types of Data Analytics Engineer jobs in Riverside, CA are:
What are popular job titles related to Junior Data Analytics Engineer jobs in Riverside, CA? For Junior Data Analytics Engineer jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Junior Data Analytics Engineer jobs in Riverside, CA look for? The top searched job categories for Junior Data Analytics Engineer jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Junior Data Analytics Engineer jobs? Cities near Riverside, CA with the most Junior Data Analytics Engineer job openings:
Infographic showing various Junior Data Analytics Engineer job openings in Riverside, CA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $74,906 per year, or $36 per hour.

Technical Architect - Data, Analytics & AI

Munich Re

Hesperia, CA โ€ข Hybrid

$63.75 - $82/hr

Other

Medical, Life, Retirement, PTO

Posted 3 days ago


Job description

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

Role Overview

We are seeking aย 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 inย 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 acrossย 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.

ย 

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)
    • AWSย  (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 isย $141,800 - $207,900ย plus opportunity for company bonus based upon a percentage of eligible pay.ย  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).ย 

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.ย