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

You will work with transit agencies, the customer success team, finance, product, company executives, and engineers. You will enable all of them to get their data questions answered in a timely ...

Associate Data Scientist

San Francisco, CA · On-site

$69K - $70K/yr

You will work with transit agencies, the customer success team, finance, product, company executives, and engineers. You will enable all of them to get their data questions answered in a timely ...

Associate Data Scientist

Palo Alto, CA · On-site

$69K - $69K/yr

You are passionate about maintaining the high scientific and engineering standards required to ... Associate Data Scientist position on our Data Science team in Palo Alto, California. Our ...

You will work with transit agencies, the customer success team, finance, product, company executives, and engineers. You will enable all of them to get their data questions answered in a timely ...

Associate Data Scientist

Palo Alto, CA · On-site

$69K - $69K/yr

You are passionate about maintaining the high scientific and engineering standards required to ... Associate Data Scientist position on our Data Science team in Palo Alto, California. Our ...

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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:

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.

Principal Associate, Data Scientist - Emerging ML

Capital One

San Jose, CA • On-site

$69K - $69K/yr

Full-time

Re-posted 8 days ago


Key responsibilities

  • Build machine learning models through all phases of development, from design to deployment, and partner with engineering teams to operationalize them in scalable production systems.

  • Partner with business and product teams to conduct experiments that improve customer experiences and business outcomes across domains like marketing, servicing, and fraud prevention.

  • Write software to collect, explore, visualize, and analyze large-scale numerical and textual data using tools like Spark and AWS.


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 148 frontline employees who took The Breakroom Quiz

89th of 175 rated banks


Job description

Principal Associate, Data Scientist - Emerging ML

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

Emerging ML is the data science and machine learning team inside Capital One's Applied Research organization. We focus on research and development of new technologies within the domain of Artificial Intelligence with a focus on Embeddings and Foundation Models. We partner closely with our product and engineering teams to connect emerging technologies with business critical use cases across Capital One's lines of business.

Role Description

This is an individual contributor position. In Emerging ML, you will work at all phases of the data science lifecycle, including:

  • Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to operationalize them in scalable and resilient production systems that serve 50+ million customers.

  • Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.

  • Write software (Python, Scala, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark and AWS.

The Ideal candidate will be:

  • Curious and creative. You thrive on bringing definition to big, undefined problems. You love asking questions, and you love pushing hard to find the answers. You're not afraid to share a new idea. You communicate clearly and effectively to share your findings with non-technical audiences.

  • Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms. You are not afraid of petabytes of data.

  • Statistically-minded. You have built models, validated them and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series analysis and deep learning.

  • Customer and product oriented. You share our passion for changing banking for good.

Basic Qualifications:

  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:

    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics

    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics

    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Preferred Qualifications:

  • Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)

  • At least 3 years of experience in Python, Scala, or R

  • At least 3 years of experience with machine learning

  • At least 3 years of experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science


New York, NY: $176,500 - $201,400 for Princ Associate, Data Science


San Jose, CA: $176,500 - $201,400 for Princ Associate, Data Science









Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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