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Associate Data Engineering Jobs in Newark, CA (NOW HIRING)

Accenture

Google Senior Data Engineer

Mountain View, CA · On-site

$94 - $266/hr

Hands‑on experience with CI/CD, Git, or cloud-native engineering practices. * Google Cloud certifications (Associate Cloud Engineer or Professional Data Engineer). * Experience working in agile ...

Qcells

Lead Data Engineer

Santa Clara, CA · On-site

$160K - $220K/yr

MINIMUM QUALIFICATIONS * 10+ years of experience in data engineering, data architecture, or related ... Azure certifications (Data Engineer Associate, Solutions Architect, or equivalent). * Experience ...

Qcells

Lead Data Engineer

Santa Clara, CA

$160K - $220K/yr

MINIMUM QUALIFICATIONS * 10+ years of experience in data engineering, data architecture, or related ... Azure certifications (Data Engineer Associate, Solutions Architect, or equivalent). * Experience ...

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All JobsAssociate Data Engineering JobsAssociate Data Engineering Jobs in Newark, CA

Associate Data Engineering information

See Newark, CA salary details

$16

$37

$63

How much do associate data engineering jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for associate data engineering in Newark, CA is $37.20, according to ZipRecruiter salary data. Most workers in this role earn between $27.60 and $44.09 per hour, depending on experience, location, and employer.

What is an associate data engineer?

An Associate Data Engineer is an entry-level professional who assists in designing, building, and maintaining data pipelines and infrastructure. They typically work with senior data engineers to ensure data is collected, stored, and processed efficiently for analytics and business use. Responsibilities often include data cleaning, integration, and supporting the development of scalable data solutions. Associate Data Engineers usually have foundational knowledge of programming, databases, and cloud technologies.

What are some typical projects an associate data engineer might work on in their first year?

In their first year, an Associate Data Engineer often works on building and maintaining data pipelines, cleaning and transforming raw data, and supporting the integration of new data sources. They may also assist in optimizing existing data workflows for better performance and reliability, as well as collaborating closely with data analysts and senior engineers to ensure data quality and accessibility. These projects help new team members develop a strong understanding of the organization's data infrastructure and best practices in data engineering.

What are the key skills and qualifications needed to thrive as an associate data engineer, and why are they important?

To thrive as an Associate Data Engineer, a solid understanding of database systems, SQL, data modeling, and a relevant bachelor's degree in computer science or a related field is essential. Familiarity with ETL tools, cloud platforms like AWS or Azure, and programming languages such as Python or Java is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help set candidates apart in collaborative, data-driven environments. These skills and qualities are crucial for building reliable data pipelines, ensuring data quality, and enabling actionable business insights.

What is the difference between Associate Data Engineering vs Data Engineer?

AspectAssociate Data EngineeringData Engineer
Required CredentialsBachelor's degree in CS, IT, or related field; some certificationsBachelor's or master's degree; extensive experience preferred
Work EnvironmentEntry-level, team-focused, supporting data pipelinesDesigning, building, and maintaining large-scale data systems
Employer & Industry UsageCommon in tech companies, finance, healthcareUsed across industries for advanced data infrastructure roles
Search & Comparison IntentEntry-level, learning, support rolesAdvanced, specialized data infrastructure roles

The main difference between Associate Data Engineering and Data Engineer lies in experience and responsibilities. Associate Data Engineers are typically entry-level, focusing on supporting data pipelines and gaining hands-on experience. Data Engineers have more experience, handling complex data architecture, optimization, and system design. Both roles require similar educational backgrounds, but Data Engineers usually have more technical expertise and responsibility.

What are the most commonly searched types of Data Engineering jobs in Newark, CA?

The most popular types of Data Engineering jobs in Newark, CA are:

What cities near Newark, CA are hiring for Associate Data Engineering jobs?

Cities near Newark, CA with the most Associate Data Engineering job openings:

Associate Data Engineering jobs near you
Infographic showing various Associate Data Engineering job openings in Newark, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Hybrid job distribution, with an average salary of $77,375 per year, or $37.2 per hour.

Associate Fraud Strategy Data Scientist

5 Star Global Recruitment Partners

San Jose, CA

$69K - $69K/yr

Full-time

Re-posted 15 days ago

Job description

Associate Fraud Strategy Data Scientist

San Jose, California, United States

Associate Fraud Strategy Data Scientist

We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Strategy team. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms preferably in the risk domain.

Wed love to chat if you have:

  • Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
  • Bachelors degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience
  • Experience using statistics and data science to solve complex business problems
  • Proficiency in SQL, Python, Excel including key data science libraries
  • Proficiency in data visualization including Tableau
  • Experience working with large datasets
  • Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau.
  • Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes
  • Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact.
  • Desirable to have experience or aptitude solving problems related to risk using data science and analytics
  • Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies

Key Job Functions

  • Design rules to detect/mitigate fraud
  • Develop python scripts and models that support strategies
  • Investigate novel/large cases
  • Identify root cause
  • Set strategy for different risk types
  • Work with product/engineering to improvement control capabilities
  • Develop and present strategies and guide execution

Expected Outcome in 6-12 months

  • Work closely with team members and stakeholders to consult, design, develop, and manage fraud strategies and rules that not only solve emerging fraud trends but also provide a great experience to end customers.
  • Utilize data analysis to design and implement fraud strategies
  • Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud solutions that operate at scale and in real time for end customers.
  • Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders.
  • Development of dashboard and visualizations to track KPI of fraud strategies implemented

Preferred Skills

  • Data analytics and models
  • Rule development
  • Dashboard Creation
  • Project Management
  • Strong Communication

Notes from Hiring Manager:

  • Strong SQL proficiency
  • Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation
  • Proficiency in AWS Quicksight and Tableau
  • Strictly contract to cover multiple leaves over a 1 yr. period.
  • Potential to extend based on business need and performance.
  • Day shift: M-F Pacific time
  • Multiple Zoom interviews (2-3) SQL assessment during 1st interview.

MUST HAVE:

  • Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
  • Bachelors degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience.
  • Experience using statistics and data science to solve complex business problems.
  • Experience in SQL, Python, Excel including key data science libraries.
  • Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation.
  • Experience in data visualization including Tableau.
  • Experience working with large datasets.

Apply