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Entry Level Data Engineering Jobs in Santa Clara, CA

Muon Space

Software Engineer, Entry-Level

San Jose, CA · On-site

$142K - $169K/yr

... data pipelines, computer vision, signal processing, cloud systems and more. They make it possible ... A bachelor's degree in computer science, aerospace engineering, computational mathematics or a ...

Salas O'Brien

Entry-level Mechanical Engineer

San Jose, CA · On-site

$75K - $85K/yr

Entry-level Mechanical Engineer At Salas O'Brien we tell our clients that we're engineered for ... engineering and consulting services. Our specialized experience includes design for data centers ...

Salas O'Brien

Entry-level Mechanical Engineer

San Jose, CA · On-site

$75K - $85K/yr

Entry Level Mechanical Engineer At Salas O'Brien we tell our clients that we're engineered for ... engineering and consulting services. Our specialized experience includes design for data centers ...

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Entry Level Data Engineering information

See Santa Clara, CA salary details

$13

$23

$36

How much do entry level data engineering jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for entry level data engineering in Santa Clara, CA is $23.77, according to ZipRecruiter salary data. Most workers in this role earn between $19.18 and $25.67 per hour, depending on experience, location, and employer.

What is an entry level data engineer?

An Entry Level Data Engineering job involves designing, building, and maintaining data pipelines that collect, process, and store data for analysis. Professionals in this role work with databases, ETL (Extract, Transform, Load) processes, and cloud platforms to ensure data is accessible and reliable. They often collaborate with data analysts and scientists to support business intelligence and machine learning initiatives. Common skills include SQL, Python, and experience with big data tools like Apache Spark or AWS. This role serves as a foundation for more advanced data engineering positions.

What types of projects and tasks can I expect to work on as an entry level data engineer?

As an Entry Level Data Engineer, you will typically assist with building data pipelines, cleaning and preparing data for analysis, and supporting the migration of data into cloud or on-premises data warehouses. Your daily tasks may include collaborating with data analysts, troubleshooting data quality issues, and learning to automate data flow processes. You’ll often work alongside more senior engineers, gaining exposure to real-world datasets and the software engineering practices that keep data infrastructure running smoothly. This hands-on experience offers a solid foundation for advanced data engineering roles as your career progresses.

What are the key skills and qualifications needed to thrive as an entry level data engineer?

To thrive as an Entry Level Data Engineer, you need a solid understanding of programming languages like Python or SQL, basic data modeling, and a relevant degree such as computer science or information technology. Familiarity with ETL tools, cloud platforms like AWS or Azure, and introductory certifications in big data technologies can be advantageous. Attention to detail, strong problem-solving abilities, and effective communication skills are valuable soft skills for this role. These competencies enable you to process and manage large data sets accurately, collaborate with teams, and support data-driven decision-making.

Are entry level data engineers still in demand?

Entry level data engineers are in high demand due to the increasing reliance on data-driven decision making across industries. Skills in SQL, Python, cloud platforms, and data pipeline tools like Apache Spark are valuable for these roles, which often offer strong job growth prospects.

What does an entry level data engineer do?

An entry level data engineer designs, builds, and maintains data pipelines and infrastructure to support data collection, storage, and processing. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making. This role often involves collaborating with data scientists and analysts to optimize data workflows and improve data quality.

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

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

What are popular job titles related to Entry Level Data Engineering jobs in Santa Clara, CA?

For Entry Level Data Engineering jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Engineering jobs in Santa Clara, CA look for?

The top searched job categories for Entry Level Data Engineering jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Entry Level Data Engineering jobs?

Cities near Santa Clara, CA with the most Entry Level Data Engineering job openings:

Entry Level Data Engineering jobs near you
Infographic showing various Entry Level Data Engineering job openings in Santa Clara, CA as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $49,442 per year, or $23.8 per hour.

Data Scientist - Fraud Detection

DataVisor

Mountain View, CA • On-site

Full-time

Medical, PTO

Posted 10 days ago

Job description

About DataVisor:
DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
Position Overview:
We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.
Key Responsibilities:
  • Develop and deploy machine learning models for fraud detection and risk assessment.
  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
  • Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
  • Collaborate with engineering and business teams to integrate ML models into production systems.
  • Continuously monitor model performance and refine algorithms to improve accuracy.
  • Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

Requirements
  • Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus.
  • Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
  • Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
  • Experience with SQL and data manipulation/analysis in large datasets.
  • Strong problem-solving skills and patience for deep-dive data exploration.
  • Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
  • Excellent communication skills and ability to work in a collaborative environment.

Nice to have
  • Familiarity with big data tools (Spark, Hadoop, Dask).
  • Knowledge of graph-based fraud detection techniques.
  • Experience with cloud platforms (AWS, GCP, Azure).

Benefits
PTO, Stock Option, Health Benefits

Apply