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Junior Data Engineering Jobs in California (NOW HIRING)

Deloitte

Lead AI and Data Science Engineer II

San Diego, CA

$108K - $143K/yr

Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment * Mentorship of junior and mid-level analysts, providing ...

Deloitte

Lead AI and Data Science Engineer II

Fresno, CA

$101K - $134K/yr

Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment * Mentorship of junior and mid-level analysts, providing ...

WelbeHealth

Sr. Data Engineer

Los Angeles, CA · On-site

$114K - $155K/yr

Mentor junior data engineers * Assist the data architect with high level business architecture that accelerates solution designs, improves quality of applications, drives data quality and ...

Welbehealth

Sr. Data Engineer

Los Angeles, CA

$114K - $155K/yr

Mentor junior data engineers * Assist the data architect with high level business architecture that accelerates solution designs, improves quality of applications, drives data quality and ...

WelbeHealth

Sr. Data Engineer

Los Angeles, CA · On-site

$114K - $155K/yr

Mentor junior data engineers * Assist the data architect with high level business architecture that accelerates solution designs, improves quality of applications, drives data quality and ...

Paul Hastings

Senior Data Engineer

Los Angeles, CA · On-site

$194K/yr

Mentor junior data engineers and promote best practices in CI/CD, version control, and release management. Proficiencies: * Advanced proficiency inAzure Data Factory,Azure Data Lake Storage (Gen2 ...

WelbeHealth

Sr. Data Engineer

Los Angeles, CA · On-site

$114K - $155K/yr

Mentor junior data engineers * Assist the data architect with high level business architecture that accelerates solution designs, improves quality of applications, drives data quality and ...

Samba

Data Scientist

San Francisco, CA

$150K - $185K/yr

You will work closely with Data Engineering, Product, and go-to-market teams. WHAT YOU'LL DO ... Mentor junior Data Scientists through code review, pairing, and structured technical feedback ...

Samba

Data Scientist

San Francisco, CA

$150K - $185K/yr

You will work closely with Data Engineering, Product, and go-to-market teams. WHAT YOU'LL DO ... Mentor junior Data Scientists through code review, pairing, and structured technical feedback ...

Samba

Data Scientist

San Francisco, CA · On-site

$150K - $185K/yr

You will work closely with Data Engineering, Product, and go-to-market teams. WHAT YOU'LL DO ... Mentor junior Data Scientists through code review, pairing, and structured technical feedback ...

DPP Tech, Inc.

Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Python for data engineering and automation. * Experience with Cloud Composer, Cloud Storage, Pub ... Mentor junior engineers (Lead role). Please share your updated resume at

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

Mentor junior data scientists and guide their model development, statistical analysis, and data science practices. * Data Engineering & Workflow Optimization - Collaborate with engineering teams to ...

Amazon

Data Engineer II - AMZ10046151

Santa Clara, CA · On-site

$169K - $205K/yr

Mentor junior data engineers. 40 hours / week, 8:00am-5:00pm, Salary Range: $169,129/year to $205,600/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on ...

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

Mentor junior data scientists and guide their model development, statistical analysis, and data science practices. * Data Engineering & Workflow Optimization - Collaborate with engineering teams to ...

Cloud BC Labs

AWS Data Engineer

Alameda, CA · On-site

$129K - $155K/yr

Proven experience in leading data engineering projects and mentoring junior Cloud BC Labs Inc is a digital transformation organization aimed at creating seamless solutions for clients to effectively ...

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Showing results 21-40

All JobsData Engineering JobsJunior Data Engineering JobsJunior Data Engineering Jobs in California

Junior Data Engineering information

See California salary details

$33.1K

$70.9K

$108.1K

How much do junior data engineering jobs pay per year?

As of Aug 6, 2026, the average yearly pay for junior data engineering in California is $70,859.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,900.00 and $79,000.00 per year, depending on experience, location, and employer.

What is the difference between Junior Data Engineering vs Data Analyst?

AspectJunior Data EngineeringData Analyst
Required SkillsBasic SQL, Python, data pipeline knowledgeData visualization, SQL, Excel
CertificationsEntry-level certifications in data engineering or related fieldsCertifications in data analysis or visualization tools
Work EnvironmentData engineering teams, IT departmentsBusiness units, marketing, finance teams
Industry UsageBuilding and maintaining data pipelines and infrastructureInterpreting data, creating reports and dashboards

Junior Data Engineering focuses on developing and maintaining data pipelines and infrastructure, requiring skills in SQL and Python. Data Analysts interpret data and create reports, often using visualization tools. While both roles work with data, Junior Data Engineers handle data flow and storage, whereas Data Analysts focus on data interpretation and insights.

What are the key skills and qualifications needed to thrive as a junior data engineer?

To thrive as a Junior Data Engineer, you need a solid understanding of data structures, SQL, and programming languages like Python or Java, often supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms (such as AWS or Azure), and data warehousing solutions is typically required. Strong problem-solving abilities, attention to detail, and effective communication help you excel in team environments and manage complex data workflows. These skills ensure you can reliably build, maintain, and optimize data pipelines that support organizational decision-making.

What does a junior data engineer do?

A Junior Data Engineer typically assists in designing, building, and maintaining data pipelines and databases to support analytics and business needs. They work with large datasets, ensuring data is collected, stored, and processed efficiently and accurately. Responsibilities often include data cleaning, ETL (Extract, Transform, Load) processes, and collaborating with data analysts and other engineers. Junior Data Engineers are usually early in their careers and work under the guidance of more experienced data engineers while developing their technical and problem-solving skills.

What are some typical challenges a junior data engineer may face when starting out, and how can they overcome them?

As a Junior Data Engineer, one common challenge is adapting to complex data infrastructure and unfamiliar tools or frameworks. You may also find it challenging to ensure data quality and consistency while working with large datasets. Collaborating closely with senior engineers and asking questions is key to overcoming these hurdles. Taking advantage of onboarding resources, documentation, and code reviews will help you learn best practices and improve your skills quickly. Embracing continuous learning and seeking feedback will set you up for long-term growth in data engineering.
What are the most commonly searched types of Data Engineering jobs in California? The most popular types of Data Engineering jobs in California are:
What are popular job titles related to Junior Data Engineering jobs in California? For Junior Data Engineering jobs in California, the most frequently searched job titles are:
What job categories do people searching Junior Data Engineering jobs in California look for? The top searched job categories for Junior Data Engineering jobs in California are:
What cities in California are hiring for Junior Data Engineering jobs? Cities in California with the most Junior Data Engineering job openings:
Junior Data Engineering jobs near you
Infographic showing various Junior Data Engineering job openings in California as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $70,859 per year, or $34.1 per hour.

Lead AI and Data Science Engineer II

Deloitte

Sacramento, CA

$109K - $144K/yr

Other

Posted 8 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

46th of 150 rated financial services

Job description

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118700 to $218600.

Qualifications:

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to ski...

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