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Data Engineering Jobs in Rohnert Park, CA (NOW HIRING)

Fabrion

Data Engineer (Founding Team)

Bodega Bay, CA · On-site

$135K - $163K/yr

Data/ETL Engineer (Founding Team) Location: San Francisco Bay Area Type: Full-Time Compensation: Competitive salary + early-stage equity Backed by 8VC, we're building a world-class team to tackle one ...

Procore

Principal Product Manager, Data

Bodega Bay, CA · On-site

Lead cross-functional collaboration with Engineering, Data Science, Data Engineering, and Go-to-Market teams through all phases of product development. * Define and track success metrics for data ...

Zenni Optical

Research & Insights Analyst

Novato, CA · Remote

$300/day

Collaborate with Data Engineering, AI/ML, Paid Marketing and Finance to connect research insights with internal datasets to identify research topics * Contribute to the team's research roadmap and ...

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All JobsData Engineering JobsData Engineering Jobs in Rohnert Park, CA

Data Engineering information

See Rohnert Park, CA salary details

$51K

$182.8K

$269.7K

How much do data engineering jobs pay per year?

As of Jul 16, 2026, the average yearly pay for data engineering in Rohnert Park, CA is $182,794.00, according to ZipRecruiter salary data. Most workers in this role earn between $147,900.00 and $188,300.00 per year, depending on experience, location, and employer.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Spark, and cloud platforms remains critical for managing data workflows and ensuring data quality.

What work does a data engineer do?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and optimized for analysis by data scientists and analysts.

What are the typical daily responsibilities of a Data Engineer?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

What engineers make 500,000?

Senior data engineers with extensive experience, specialized skills in cloud platforms, and advanced knowledge of data architecture can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes stock options or bonuses.

What is a Data Engineering job?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically require skills in SQL, cloud platforms, and data pipeline tools like Apache Spark or Kafka, making their expertise valuable across many industries. The role is expected to remain strong as organizations continue to prioritize data infrastructure and analytics capabilities.

What are the key skills and qualifications needed to thrive in the Data Engineering position, and why are they important?

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

What job categories do people searching Data Engineering jobs in Rohnert Park, CA look for? The top searched job categories for Data Engineering jobs in Rohnert Park, CA are:
What cities near Rohnert Park, CA are hiring for Data Engineering jobs? Cities near Rohnert Park, CA with the most Data Engineering job openings:
Data Engineering jobs near you
Infographic showing various Data Engineering job openings in Rohnert Park, CA as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $182,794 per year, or $87.9 per hour.
Machine Learning/AI Engineer Lead

Machine Learning/AI Engineer Lead

Nexwave

Santa Rosa, CA • On-site

$75/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Role : Machine Learning/AI Engineer (Lead)


Location :: Alpharetta GA (OR) Oakland Bay area , CA (weekly one day in office)

Exp Req : 15-20 Yrs Max


Visa : USC/GC/GC EAD


Rate : $75/Hr on C2C/1099


Role Summary


We are seeking a hands-on Machine Learning / AI Engineer to lead the adoption, governance, and productionization of ML and AI solutions within a leading Dental Insurance organization. This role will serve as the technical advisor and mentor for citizen data scientists and ML practitioners, establishing best practices, scalable architectures, and operational frameworks for AI/ML solutions. The ideal candidate has strong experience with Snowflake, Azure Machine Learning, MLOps, and enterprise AI platforms.


Key Responsibilities

Define and implement enterprise best practices for Machine Learning, Generative AI, and MLOps.

Partner with business, product, data engineering, and analytics teams to identify and prioritize AI/ML use cases.

Guide citizen data scientists and analysts in developing production-ready ML solutions.

Design, build, and operationalize ML models and AI solutions using Snowflake and Azure ML.

Establish model governance, monitoring, versioning, explainability, and model lifecycle management processes.

Collaborate with Data Engineering teams to build scalable feature engineering and data pipelines.

Evaluate and recommend AI/ML tools, frameworks, and architectural patterns.

Support deployment and operationalization of predictive analytics, NLP, GenAI, and intelligent automation use cases.

Ensure compliance with security, privacy, and regulatory requirements in a healthcare/insurance environment.


Required Qualifications

7+ years of experience in Data Science, Machine Learning, or AI Engineering.

Strong hands-on experience with Azure Machine Learning and MLOps.

Experience working with Snowflake, including Snowpark, ML capabilities, and AI features.

Proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.

Experience deploying and monitoring ML models in production environments.

Strong understanding of feature engineering, model governance, and model lifecycle management.

Excellent communication and stakeholder management skills.


Preferred Qualifications

Experience in Healthcare or Insurance domains (Dental Insurance preferred).

Experience with Generative AI, LLMs, RAG architectures, and AI governance.

Familiarity with Azure OpenAI, Snowflake Cortex, and enterprise AI platforms.


Regards,

Stephen

Lead Talent Acquisition Specialist

Email : stephen@nexwaveinc.com

Apply