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Hadoop Python Jobs in Reston, VA (NOW HIRING)

Accord Technologies Inc.

Data Engineer II

Arlington, VA · On-site

$131K - $158K/yr

Banking/Financial, Big Data, Data Modeling, ETL, Hadoop, Python, Spark, SQL , The ideal candidate must have 9+ years of hands-on data engineering experience building large-scale ETL pipelines using ...

New

Delan Associates, Inc

Data Engineer II (Remote)

Arlington, VA · Remote

$117K - $140K/yr

Spark, Hadoop, and Python are the skills required for the role. It will be hybrid, 3 days a week in office. Please Focus on local resources or candidates within a commutable distance to Arlington ...

New

Delan Associates, Inc.

Data Engineer II

Arlington, VA · On-site +1

$131K - $158K/yr

Spark, Hadoop, and Python are the skills required for the role. It will be hybrid, 3 days a week in office. Please Focus on local resources or candidates within a commutable distance to Arlington ...

New

Delan Associates, Inc

Data Engineer II

Arlington, VA · On-site

$131K - $158K/yr

Spark, Hadoop, and Python are the skills required for the role. It will be hybrid, 3 days a week in office. Please Focus on local resources or candidates within a commutable distance to Arlington ...

New

Stem Staffing LLC

Senior Data Engineer II

Arlington, VA · On-site

$122K - $165K/yr

Spark Hadoop Python Summary Role: • Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base. • Develop scalable and efficient ...

New

Alliance Sourcing Network

Data Engineer

Arlington, VA · On-site

$131K - $158K/yr

The ideal candidate must have 8+ years of hands-on data engineering experience building large-scale ETL pipelines using Apache Spark, Hadoop, Python, and SQL. They also need a strong background in ...

New

Polar IT Services

AWS Python Developer

Reston, VA · Hybrid

$52.25 - $72/hr

AWS Python Developer with AI experience Location: Reston, VA Mode of Work: 3 Days hybrid Top Skills ... Knowledge of big data technologies ( Spark, Hadoop, Databricks). Background in NLP, computer vision ...

Polar IT Services

AWS Python Developer

Reston, VA · On-site +1

$52.25 - $72/hr

AWS Python Developer with AI experience Location: Reston, VA Mode of Work: 3 Days hybrid Top Skills ... Knowledge of big data technologies ( Spark, Hadoop, Databricks). Background in NLP, computer vision ...

Compunnel

Big Data Platform Engineer

Rockville, MD · On-site

$56.75 - $75.25/hr

Key Responsibilities • Design, develop, and maintain large-scale data processing pipelines using Apache Spark, Hadoop, Python, and Scala. • Architect, deploy, and optimize containerized big data ...

New

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Hadoop Python information

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How much do hadoop python jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for hadoop python in Reston, VA is $62.31, according to ZipRecruiter salary data. Most workers in this role earn between $59.28 and $68.03 per hour, depending on experience, location, and employer.

Is Hadoop admin a good career?

Hadoop administration is a viable career path for those interested in managing big data infrastructure, requiring skills in Hadoop ecosystem tools, Linux, and scripting. It offers opportunities in data management, analytics, and cloud environments, with demand driven by data-driven business needs. Certifications like Cloudera or Hortonworks can enhance job prospects.

Are Python still in demand in 2026?

Python remains highly in demand for roles like Hadoop Python developers, as it is widely used for data processing, scripting, and automation in big data environments. Its versatility and strong community support ensure continued relevance, especially when combined with skills in Hadoop, Spark, and cloud platforms.

Does Hadoop work with Python?

Hadoop can work with Python through tools like Hadoop Streaming, which allows Python scripts to process data within Hadoop jobs. Additionally, frameworks such as PySpark enable Python developers to work with Apache Spark on Hadoop clusters for big data processing. Knowledge of these tools is beneficial 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.

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.
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What cities near Reston, VA are hiring for Hadoop Python jobs? Cities near Reston, VA with the most Hadoop Python job openings:
Hadoop Python jobs near you
Data Engineer II

Data Engineer II

Accord Technologies Inc.

Arlington, VA • On-site

$131K - $158K/yr

Contractor

Posted 6 days ago

New

Job description

Title: Data Engineer II
Location : Arlington, VA, (Onsite) 
Position type: W2 contract
Industry: Banking/Financials/Payments
 
Mandatory: Banking/Financial, Big Data, Data Modeling, ETL, Hadoop, Python, Spark, SQL , 

Job Description:
The ideal candidate must have 9+ years of hands-on data engineering experience building large-scale ETL pipelines using Apache Spark, Hadoop, Python, and SQL. They also need a strong background in the payments or financial sector, paired with excellent communication skills to effectively influence and partner with cross-functional teams.
 
Required Education
• Bachelor's degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may also be considered.
Required Qualifications/Skills/Experience:
• Experience as a Data Engineer or in a similar role, with a strong understanding of data engineering concepts and methodologies.
• Strong knowledge of writing and optimizing SQL queries to retrieve, manipulate, and analyze data efficiently.
• Hands-on experience with big data technologies such as:
• Apache Spark (PySpark, Spark SQL, Spark Streaming)
• Hadoop ecosystem (HDFS/ Ozone, Hive, YARN)
• Understanding data modeling concepts and database design to support scalable data solutions.
• Familiarity with Python.
• Ability to analyze and troubleshoot data issues and provide solutions with minimal supervision.
• Basic knowledge of testing and validating data to ensure accuracy and consistency in data pipelines.
• Excellent verbal and written communication skills, with the ability to articulate complex ideas clearly and concisely to both technical and non-technical stakeholders.
Role:
This role focuses on designing, implementing, and maintaining scalable enterprise ETL processes and robust data pipelines for a global client base. You will leverage big data frameworks like Apache Spark and Hadoop, along with SQL and Python, to optimize data processing and ensure high data quality. Working closely with cross-functional teams, you will automate routine tasks and deliver accurate, high-value data solutions across various industries.
• Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.
• Develop scalable and efficient code to process data, ensuring availability and accessibility in a timely manner.
• Leverage big data processing frameworks such as Apache Spark and Hadoop to build and optimize data pipelines.
• Collaborate with senior engineers to address data challenges, contributing to solutions that maintain high data quality.
• Assist in the data delivery process, working alongside Data Engineers and Analysts to support accurate, high-value data solutions across various clients and industries.
• Build strong working relationships with team members and clients, contributing to both local and global projects.
• Learn and apply industry best practices, including version control, code reviews, and data validation, to ensure quality in data processes.
• Use SQL and other database technologies to help optimize data processing and reduce the time required to handle large data sets.
• Design, implement, and maintain data pipelines using ETL frameworks, orchestration tools, and distributed data processing engines.
• Participate in efforts to automate routine data tasks and streamline processes.
• Comply with all Mastercard internal policies and adhere to external regulations.