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Hadoop Python Jobs in Rio Linda, CA (NOW HIRING)

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Hadoop Python information

See Rio Linda, CA salary details

$11

$66

$81

How much do hadoop python jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for hadoop python in Rio Linda, CA is $66.39, according to ZipRecruiter salary data. Most workers in this role earn between $63.17 and $72.50 per hour, depending on experience, location, and employer.

Is Hadoop a good career?

Hadoop Python roles involve working with big data processing using Hadoop frameworks and Python programming. These jobs are in demand in data-driven industries, often requiring knowledge of distributed systems, data analysis, and related tools like Spark or Hive. Careers in this field can offer growth opportunities with relevant certifications and experience in data engineering or analytics.

Does Hadoop work with Python?

Hadoop can work with Python through tools like Hadoop Streaming, which allows developers to write MapReduce jobs in Python. Additionally, frameworks such as PySpark enable Python integration with Apache Spark, often used alongside Hadoop for big data processing. Knowledge of these tools is valuable for Hadoop Python roles.

What are the key skills and qualifications needed to thrive as a Hadoop Python Developer, and why are they important?

To thrive as a Hadoop Python Developer, you need a strong understanding of distributed computing, Hadoop ecosystem components (like HDFS, MapReduce, Hive, or Pig), and advanced Python programming skills, often supported by a degree in computer science or related field. Familiarity with tools such as Apache Spark, Sqoop, and workflow schedulers (like Oozie or Airflow), along with experience in handling big data platforms, is typically required. Problem-solving abilities, attention to detail, and effective communication help developers collaborate with teams and translate business requirements into scalable data solutions. These skills and qualifications are essential for efficiently processing and analyzing large datasets, ensuring data reliability, and driving business insights.

What is the highest paying job in Python?

The highest paying Python-related jobs include roles such as Machine Learning Engineer, Data Scientist, and Quantitative Analyst, often requiring advanced skills in algorithms, statistics, and frameworks like TensorFlow or scikit-learn. These positions typically offer salaries exceeding $120,000 annually, especially with experience and relevant certifications.

What is the difference between Hadoop Python vs Hadoop Java Developer?

AspectHadoop PythonHadoop Java Developer
Required CredentialsPython programming skills, Hadoop certificationsJava programming skills, Hadoop certifications
Work EnvironmentData analysis, scripting, data pipeline developmentCore development, system integration, big data application coding
Industry UsageData science, analytics, machine learning projectsData infrastructure, platform development, system optimization

Hadoop Python and Hadoop Java Developer roles both involve working with Hadoop ecosystems, but Python focuses more on data analysis and scripting, while Java is geared towards core development and system integration. The choice depends on your programming expertise and career goals within big data environments.

What is a Hadoop Python developer?

A Hadoop Python developer is a software professional who specializes in using Python programming language to develop, implement, and maintain applications that process and analyze large datasets within the Hadoop ecosystem. They leverage Python libraries like PySpark to write scalable data processing scripts, interact with Hadoop components such as HDFS, and optimize big data workflows. These developers play a critical role in building data pipelines, performing data transformation, and supporting analytics projects in organizations that handle vast amounts of data.

What is the salary of Hadoop engineer?

The salary of a Hadoop engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and certifications. Skilled professionals with expertise in big data tools and programming languages like Python can command higher salaries in this field.

How do Hadoop Python developers typically collaborate with data engineers and analysts on large-scale data projects?

Hadoop Python developers frequently work alongside data engineers and analysts to design, implement, and optimize data pipelines for handling vast datasets. They are responsible for writing Python scripts that interface with Hadoop components, ensuring data is processed efficiently and meets project requirements. Regular communication with data engineers helps align on infrastructure and architectural decisions, while close collaboration with analysts ensures data outputs are accurate and actionable. Agile methodologies and daily stand-ups are common, fostering teamwork and quick problem-solving.
What cities near Rio Linda, CA are hiring for Hadoop Python jobs? Cities near Rio Linda, CA with the most Hadoop Python job openings:
Hadoop Python jobs near you
Infographic showing various Hadoop Python job openings in Rio Linda, CA as of June 2026, with employment types broken down into 6% Internship, 78% Full Time, 5% Part Time, 3% Temporary, 7% Contract, and 1% Nights. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $138,089 per year, or $66.4 per hour.
ETL Tester (Automation) -Big Data / || Woodland Hills, CA (Hybrid)

ETL Tester (Automation) -Big Data / || Woodland Hills, CA (Hybrid)

Empower Professionals

Woodland, CA • On-site

$46.25 - $61.25/hr

Other

Posted 9 days ago

Job description

Role: ETL Tester (Automation)- Big Data / 

Location:  Woodland Hills, CA (Hybrid)

Duration: 12+ Month

Required Skills

•              Strong experience in ETL testing / Data Warehouse testing

•              Proficiency in Python for automation (Pytest, Pandas, or similar frameworks)

•              Strong SQL skills for data validation and analysis

•              Hands-on experience with Big Data technologies such as Hadoop, Hive, Spark, or similar

•              Experience validating data across multiple data sources and formats

•              Knowledge of data pipelines, transformations, and ETL workflows

•              Exposure to API testing / data ingestion validation

•              Familiarity with CI/CD tools (Jenkins, Git, etc.)

•              Strong understanding of Agile methodology

 

Thanks

Yashasvi Hasija

Team Lead | Empower Professionals

......................................................................................................................................

   | Phone:  x 368 | Fax:

LinkedIn: linkedin.com/in/yashasvi-hasija-6a745625b

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